diff --git a/.all_crates.sh b/.all_crates.sh
index 859bbff144..8ba76a3531 100644
--- a/.all_crates.sh
+++ b/.all_crates.sh
@@ -1,2 +1,2 @@
 
-ALL_CRATES_PATH="data linalg core nnef nnef/nnef-resources pulse-opl pulse extra transformers hir tflite tensorflow onnx-opl onnx gpu metal cuda libcli api api/rs api/ffi api/proxy/sys api/proxy cli"
+ALL_CRATES_PATH="data linalg core nnef nnef/nnef-resources transformers pulse-opl pulse extra hir tflite tensorflow onnx-opl onnx gpu metal cuda libcli api api/rs api/ffi api/proxy/sys api/proxy cli"
diff --git a/.github/scripts/inject_wheel_sboms.py b/.github/scripts/inject_wheel_sboms.py
new file mode 100644
index 0000000000..fcb6c17f47
--- /dev/null
+++ b/.github/scripts/inject_wheel_sboms.py
@@ -0,0 +1,85 @@
+"""Inject CycloneDX + SPDX SBOMs into a wheel's `.dist-info/sboms/` per PEP 770.
+
+Reads the wheel, generates SBOMs from its unpacked contents via `syft`
+(which understands the `cargo-auditable` section embedded in the
+bundled Rust dylib), drops them into the wheel's metadata directory,
+and re-packs the wheel.  `wheel pack` regenerates RECORD so the new
+files are properly listed and hashed.
+
+Usage:  python inject_wheel_sboms.py wheel-1.whl wheel-2.whl ...
+        (in-place; replaces each input wheel with the SBOM-bearing one)
+
+Requires:  `syft` on PATH, and the `wheel` Python package installed.
+"""
+
+import shutil
+import subprocess
+import sys
+import tempfile
+from pathlib import Path
+
+
+def inject(wheel_path: Path) -> None:
+    wheel_path = wheel_path.resolve()
+    with tempfile.TemporaryDirectory() as tmp:
+        tmp = Path(tmp)
+        unpack_root = tmp / "unpacked"
+        repack_root = tmp / "repacked"
+        unpack_root.mkdir()
+        repack_root.mkdir()
+
+        subprocess.check_call(
+            [sys.executable, "-m", "wheel", "unpack", "-d", str(unpack_root), str(wheel_path)]
+        )
+
+        # `wheel unpack` writes one top-level dir named `<name>-<version>`
+        (unpacked,) = list(unpack_root.iterdir())
+        (dist_info,) = list(unpacked.glob("*.dist-info"))
+
+        sboms_dir = dist_info / "sboms"
+        sboms_dir.mkdir(exist_ok=True)
+
+        # syft scans the unpacked tree.  Its rust-audit-binary cataloger
+        # reads the `.dep-v0` ELF/Mach-O section that `cargo-auditable`
+        # embedded; the Python cataloger picks up METADATA.
+        subprocess.check_call(
+            [
+                "syft",
+                "scan",
+                f"dir:{unpacked}",
+                "--source-name",
+                unpacked.name,
+                "-o",
+                f"cyclonedx-json={sboms_dir / 'sbom.cdx.json'}",
+                "-o",
+                f"spdx-json={sboms_dir / 'sbom.spdx.json'}",
+            ]
+        )
+
+        # `wheel pack` rewrites RECORD with hashes for every file under
+        # `unpacked/`, including the two SBOMs we just added.
+        subprocess.check_call(
+            [sys.executable, "-m", "wheel", "pack", "-d", str(repack_root), str(unpacked)]
+        )
+
+        (repacked_wheel,) = list(repack_root.glob("*.whl"))
+        # Names should match; if `wheel pack` produced a different
+        # filename (e.g. build-tag difference), prefer the new name.
+        target = wheel_path.parent / repacked_wheel.name
+        if target != wheel_path:
+            wheel_path.unlink()
+        shutil.move(str(repacked_wheel), str(target))
+        print(f"injected SBOMs into {target.name}")
+
+
+def main(argv: list[str]) -> int:
+    if not argv:
+        print(__doc__, file=sys.stderr)
+        return 2
+    for w in argv:
+        inject(Path(w))
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main(sys.argv[1:]))
diff --git a/.github/workflows/binaries.yml b/.github/workflows/binaries.yml
index 6d91302454..f2837a1265 100644
--- a/.github/workflows/binaries.yml
+++ b/.github/workflows/binaries.yml
@@ -22,6 +22,11 @@ jobs:
     name: Upload Release Binaries
     permissions:
       contents: write
+      # OIDC + attestations: cryptographically sign each released .tgz
+      # against its SBOMs via GitHub's attestation store.  Anyone can
+      # then verify with `gh attestation verify <tgz> --owner sonos`.
+      id-token: write
+      attestations: write
     strategy:
       fail-fast: false
       matrix:
@@ -98,15 +103,59 @@ jobs:
             export CARGO_TARGET_${RUST_TRIPLE_ENV}_LINKER=$TARGET_CC
           fi
 
-          cargo build --target ${target} --release -p tract-cli
+          # cargo-auditable wraps `cargo build` to embed the resolved
+          # dependency graph into the binary so consumers can recover
+          # the SBOM directly from the binary via `cargo audit bin`.
+          cargo install --locked cargo-auditable --version 0.7.0
+          cargo auditable build --target ${target} --release -p tract-cli --locked
           mkdir tract-$name
           cp target/${target}/release/tract tract-${name}
           tar czf tract-${name}.tgz tract-${name}
 
+      - name: Generate CycloneDX SBOM
+        uses: anchore/sbom-action@e22c389904149dbc22b58101806040fa8d37a610 # v0.24.0
+        with:
+          path: .
+          format: cyclonedx-json
+          artifact-name: tract-${{ matrix.target }}-${{ steps.version.outputs.value }}.cdx.json
+          output-file: tract-${{ matrix.target }}-${{ steps.version.outputs.value }}.cdx.json
+          upload-artifact: false
+          upload-release-assets: false
+
+      - name: Generate SPDX SBOM
+        uses: anchore/sbom-action@e22c389904149dbc22b58101806040fa8d37a610 # v0.24.0
+        with:
+          path: .
+          format: spdx-json
+          artifact-name: tract-${{ matrix.target }}-${{ steps.version.outputs.value }}.spdx.json
+          output-file: tract-${{ matrix.target }}-${{ steps.version.outputs.value }}.spdx.json
+          upload-artifact: false
+          upload-release-assets: false
+
+      - name: Attest build provenance
+        uses: actions/attest-build-provenance@a2bbfa25375fe432b6a289bc6b6cd05ecd0c4c32 # v4.1.0
+        with:
+          subject-path: tract-${{ matrix.target }}-${{ steps.version.outputs.value }}.tgz
+
+      - name: Attest release tarball with CycloneDX SBOM
+        uses: actions/attest-sbom@c604332985a26aa8cf1bdc465b92731239ec6b9e # v4.1.0
+        with:
+          subject-path: tract-${{ matrix.target }}-${{ steps.version.outputs.value }}.tgz
+          sbom-path: tract-${{ matrix.target }}-${{ steps.version.outputs.value }}.cdx.json
+
+      - name: Attest release tarball with SPDX SBOM
+        uses: actions/attest-sbom@c604332985a26aa8cf1bdc465b92731239ec6b9e # v4.1.0
+        with:
+          subject-path: tract-${{ matrix.target }}-${{ steps.version.outputs.value }}.tgz
+          sbom-path: tract-${{ matrix.target }}-${{ steps.version.outputs.value }}.spdx.json
+
       - name: Upload asset
         uses: softprops/action-gh-release@b4309332981a82ec1c5618f44dd2e27cc8bfbfda # v3
         with:
-          files: tract-${{matrix.target}}-${{ steps.version.outputs.value }}.tgz
+          files: |
+            tract-${{matrix.target}}-${{ steps.version.outputs.value }}.tgz
+            tract-${{matrix.target}}-${{ steps.version.outputs.value }}.cdx.json
+            tract-${{matrix.target}}-${{ steps.version.outputs.value }}.spdx.json
           name: ${{ steps.version.outputs.value }}
           tag_name: v${{ steps.version.outputs.value }}
         env:
diff --git a/.github/workflows/pydoc.yml b/.github/workflows/pydoc.yml
index f362fb08b0..73f3585a58 100644
--- a/.github/workflows/pydoc.yml
+++ b/.github/workflows/pydoc.yml
@@ -85,13 +85,16 @@ jobs:
               json.dump(versions, f, indent=2)
           "
 
-          # commit and push
+          # commit and push. actions/checkout ran with persist-credentials:
+          # false, so no auth is wired into .git/config — push via an
+          # explicit token URL instead.
           git add -A
           git commit -m "Update Python docs ($version)" || true
-          git push origin gh-pages
+          git push "https://x-access-token:${GH_TOKEN}@github.com/${GITHUB_REPOSITORY}.git" gh-pages
 
           # clean up worktree
           cd -
           git worktree remove "$workdir"
         env:
           STEPS_VERSION_OUTPUTS_VALUE: ${{ steps.version.outputs.value }}
+          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
diff --git a/.github/workflows/wheels.yml b/.github/workflows/wheels.yml
index e9cd14640a..2f68ba9a74 100644
--- a/.github/workflows/wheels.yml
+++ b/.github/workflows/wheels.yml
@@ -63,6 +63,18 @@ jobs:
           timeout_seconds: 54000 # 15 hours :/
           command: uvx cibuildwheel --output-dir wheelhouse api/py
 
+      - name: Install syft
+        uses: anchore/sbom-action/download-syft@e22c389904149dbc22b58101806040fa8d37a610 # v0.24.0
+
+      - name: Inject CycloneDX + SPDX SBOMs into wheels (PEP 770)
+        shell: bash
+        run: |
+          set -ex
+          uv pip install --system wheel
+          for w in wheelhouse/*.whl ; do
+            python .github/scripts/inject_wheel_sboms.py "$w"
+          done
+
       - uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7
         with:
           name: wheels-${{github.run_id}}-${{matrix.os}}
diff --git a/.gitignore b/.gitignore
index eca6887263..226275610d 100644
--- a/.gitignore
+++ b/.gitignore
@@ -2,7 +2,6 @@ target
 **/*.rs.bk
 *.rustfmt
 *.back
-Cargo.lock
 examples/data
 .idea
 .cached/**
diff --git a/.travis/cargo-deny-check.sh b/.travis/cargo-deny-check.sh
index 6f6e082bb7..a1e61f446a 100755
--- a/.travis/cargo-deny-check.sh
+++ b/.travis/cargo-deny-check.sh
@@ -7,4 +7,7 @@ else
     CARGO_DENY="cargo deny"
 fi
 
-(cd api/rs ; $CARGO_DENY check)
+set -e
+
+(cd api/rs ; $CARGO_DENY check -c deny.toml)
+(cd cli ; $CARGO_DENY check -c deny.toml)
diff --git a/.travis/tf.sh b/.travis/tf.sh
deleted file mode 100755
index 2d20db30e6..0000000000
--- a/.travis/tf.sh
+++ /dev/null
@@ -1,11 +0,0 @@
-#!/bin/sh
-
-set -ex
-
-if [ -z "$CACHEDIR" ]
-then
-    CACHEDIR=`dirname $0`/../.cached
-fi
-
-
-(cd tensorflow; cargo test --release --features conform)
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 85f47820ca..ecbb0bb388 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,22 +1,48 @@
-# 0.23.0 — soon
+
+# 0.22.x → 0.23 in a nutshell
+
+- **`tract` facade is now the recommended public API.** Renamed from `tract-rs`; sole crate under semver, one curated surface (`Model`/`Runnable`/`State`/`Tensor`/`TDim` + `nnef()`/`onnx()`/`runtime_for_name`). `ndarray` removed from public types in favour of opt-in `impl_ndarray_interop!()`. Most other API renames in this release fall out of this consolidation (`Value`→`Tensor`, `concretize_symbols`→`set_symbols`, `default` runtime → `cpu`, …).
+- **GPU is first-class.** `cuda` + `metal` `Runtime` impls with f16 conv + cuDNN, CUDA 13 (CUDA 12 dropped), automatic per-node CPU fallback when GPU rejects a shape; virtual `gpu` / `gpu-or-cpu` names for portable downstream code.
+- **Supply-chain hardening.** ` Cargo.lock` tracked; CDX + SPDX SBOMs on release binaries plus PEP 770 SBOMs in wheels (`cargo-auditable` + GitHub attestations);
+
+## Migrating from 0.22.x to 0.23
+
+For normal usage we recommend adopting the **`tract` facade crate** (the public API at `api/rs`) instead of wiring `tract-core`, `tract-nnef`, `tract-onnx`, `tract-pulse`, `tract-cuda`, `tract-metal`, etc. directly. The facade exposes one stable surface — `nnef()`, `onnx()`, `runtime_for_name("cpu" | "gpu" | "gpu-or-cpu" | "cuda" | "metal" | ...)`, plus `Model`, `Runnable`, `State`, `Tensor`, `TDim`, and a `SetSymbols` transform builder — with all the backends curated behind it. `impl_ndarray_interop!()` (0.23.0-dev.5) keeps `ndarray` interop opt-in without leaking an `ndarray` version into the public API. Downstream code that pinned `tract-core` + `tract-onnx` directly can usually drop those deps in favour of `tract = "0.23"` and `use tract::prelude::*;`. Examples are now organised around this facade — see `examples/onnx-mobilenet-v2`, `examples/nnef-mobilenet-v2`, and `examples/causal_llm`.
+
+# 0.23.0 - 2026-05-1
+
+This section lists changes since 0.23.0-dev.5 only; the dev.2…dev.5 sections below cover the rest of the 0.22.x→0.23.0 delta.
+
+### API — breaking
+
+- **`concretize_symbols` / `substitute_symbols` renamed to `set_symbols`.** Affects `TypedModel::set_symbols`, the `SetSymbols` transform (was `ConcretizeSymbols`), and the `--transform set_symbols=...` CLI form. No deprecation aliases — call sites must be updated.
+- **`default` runtime renamed to `cpu`.** `runtime_for_name("default")` still resolves to the CPU runtime (ad-hoc alias), but `Runtime::name()` returns `"cpu"`. JSON loading configs and `--loading-config-path` payloads that pin `"default"` keep working.
+- **`nnef().with_tract_core()` removed.** The `tract_core` extension is opt-out since 0.23.0-pre — call `disable_tract_core()` instead, or just drop the `with_tract_core()?` line.
+
 
 ### CPU / linalg
 
 - **ARM SME backend (ARMv9.2-A).** New `linalg/arm64/sme` module provides SME GEMM (Phase 1) and SME2 GEMV (`sme_mmv_f32_64x1`, Phase 2A) micro-kernels for Apple M4+, Cortex-X4, and other ARMv9.2-A+ chips. Dispatch is gated on a 512-bit streaming vector length at runtime; SME2 assembler detection skips kernels when the assembler lacks support. Force via `TRACT_CPU_AARCH64_KIND=applem` (or `generic` to disable).
+- **ARMv9 SVE**: f32/f16 GEMM+GEMV and int8→i32 GEMM+GEMV kernels
 - **Apple AMX: shape-aware dispatch.** AMX kernel selection is now M/N/K-aware at runtime, yielding 5–43% wins across canary models.
 - **NEON element-wise kernels.** `HardSwish`, `SiLU`, and `GELU` get dedicated aarch64 NEON kernels wired as single graph ops.
 - **x86_64.** M-aware kernel picker; AVX-512 GEMM routed to the 16×8 / 32×5 / 32×6 kernels.
 - **WASM SIMD.** Relaxed-SIMD FMA in all MMM kernels; 32×1 GEMV kernel (8 v128 accumulators, 8-way ILP); vectorised sigmoid and tanh; `rustfft wasm_simd` enabled. Low-accumulator MMM paths recover 8–23% under `+relaxed-simd`; M-band GEMV dispatch woken up (30–37% on small-M). `Executor::RayonGlobal` for `wasm-bindgen-rayon`.
+- **WASM**: relaxed-dot int8 fast path + PackedI8K4 + SIMD int8 matmul.
 - **Multithreaded GEMM.** TLS borrow and sync hoisted out of the per-tile inner loop; 2D chunked dispatch with a small-MMM threshold avoids rayon overhead on small operands.
 - **im2col.** Contiguous-x fast path for valid (zero-padding, unit stride) convolutions; grouped lazy im2col extended; depthwise convolutions excluded from lazy im2col path; N=1/2/3 zone dispatch for depthwise.
 - **General.** Same-shape fast path in `BinMiniOp::generic_eval`; `rbytes=96/128` fast paths for mn-major packing.
 - **EinSum** Fold contiguous same-role axes in standard codegen.
 - **BLAS / SGemm integration dropped.**
+- **Cache-adaptive 2D-blocking** for the single-thread MMM tile walk; per-OS L2-size detection on Linux.
 
 ### ONNX
 
 - `Resize`: `pytorch_half_pixel` coordinate transformer.
 - `Reshape` with 0-dims and rank change fixed (issue #2104).
+-  Support for GroupQueryAttention, MultiHeadAttention, MatMulNBits (4-bit), SkipLayerNormalization, SimplifiedLayerNormalization, BiasGelu / FastGelu /
+  QuickGelu, LpNormalization, MeanVarianceNormalization, GroupNormalization, RotaryEmbedding, opset-24 Attention, Swish, Mish, Gelu, RMSNormalization.
+- LayerNorm: fixed output dtype mismatch with F16 inputs.
 
 ### NNEF
 
@@ -26,16 +52,20 @@
 ### Pulse for chunked attention layers (experimental)
 
 - **`pulse::Blockify` rewrite pass.** Translates block-diagonal multi-time-axis subgraphs into chunk-parallel form: recognises quadratic sections (EinSum terminators, `DiagGather` initiators, banded masks, Softmax body chains) and rewrites each into a per-chunk section. Covered by ex01–ex10 synthetic harness cases.
-- **`DiagGather` op** (moved from `transformers` into `core`): causal skew-trick gather with ROI-driven narrowing and re-anchoring.
+- **`DiagGather` op**: causal skew-trick gather with ROI-driven narrowing and re-anchoring.
 - **`WindowOnAxis` op**: windowed gather over the streaming axis with configurable pad value.
 - **`AxisOp::Reshape` pulsifier**: auto-inserts alignment `Delay` on streaming-axis size change.
 - Stream-axis LCM merge + slope-based per-pulse sizing for `Range`.
+- **Scan body state reused across iterations** instead of reallocated per step.
+- **`scaled_masked_softmax`** gains a `bool`-mask variant and a `post_softmax_mask` variant on both cuda and metal.
+- **`GpuPulsePad`**: stride-aware initial copy fixes 26% drift on pulsified encoders where a fused move axis fed a non-contiguous view to the pad.
 
 ### Runtime / plan
 
 - Per-node shape resolve skipped once all symbols are bound.
 - `TDim::Sym` fast-path in shape resolve; lock-free `guess_scenario` on empty scope.
 - `PropagateRoi` iterates to fixed point and simplifies.
+- **Virtual runtime names `gpu` and `gpu-or-cpu`.** `runtime_for_name("gpu")` returns the first available GPU backend (cuda or metal) or errors; `"gpu-or-cpu"` falls back to CPU if none is present.
 
 ### Scan
 
@@ -53,7 +83,17 @@
 - `doc/symbolic-shapes.md`: TDim, Symbol, and how to bind them.
 - `doc/op.md`: working with a `Tensor`'s data.
 - `doc/cli-recipe.md`: `--audit-json`, `--save-outputs`, timing pitfalls, environment-variable table.
-- `README.md`: refreshed — current backends, modern examples table, Python bindings section, torch-to-nnef pointer.
+- `README.md`: refreshed — current runtimes, modern examples table, Python bindings section, torch-to-nnef pointer.
+
+### Supply chain / build / CI
+
+- **`Cargo.lock` tracked.** All workspace + binary builds are now reproducible against the same dependency snapshot.
+- **SBOMs on release binaries (CycloneDX + SPDX).** `tract-cli` release binaries are built with `cargo-auditable` (Rust dep tree embedded in the `.dep-v0` section) and shipped alongside CDX + SPDX SBOMs generated by `syft`. Both SBOMs are signed via GitHub attestations (`actions/attest-sbom` + `actions/attest-build-provenance`).
+- **PEP 770 SBOMs in Python wheels.** Wheels are built with `cargo-auditable` and have `sbom.cdx.json` + `sbom.spdx.json` injected into `.dist-info/sboms/` per PEP 770.
+- **Release builds pinned to current stable rustc** via `dtolnay/rust-toolchain@stable`.
+- **`cargo-deny` lints wired up for `tract-cli`.**
+- **zizmor SARIF upload** to GitHub's security tab.
+
 
 # 0.23.0-dev.5 - 2026-04-22
 
@@ -146,7 +186,7 @@
 - **`into_tract()` renamed to `into_model()`** in all API layers.
 - **`DatumType` variant names shortened** — the `TRACT_DATUM_TYPE_` prefix is dropped (C API).
 - **Deprecated state methods removed**: `init_states()`, `state_initializers`, and the `n_states` parameter are gone from `State` trait and `RunTensors`.
-- **Python**: `concretize_symbols` and `pulse` methods replaced by typed transform classes; `TransformSpec` is now an abstract base class.
+- **Python**: `set_symbols` and `pulse` methods replaced by typed transform classes; `TransformSpec` is now an abstract base class.
 
 ### Improvements
 
diff --git a/Cargo.lock b/Cargo.lock
new file mode 100644
index 0000000000..be065fa77c
--- /dev/null
+++ b/Cargo.lock
@@ -0,0 +1,6000 @@
+# This file is automatically @generated by Cargo.
+# It is not intended for manual editing.
+version = 4
+
+[[package]]
+name = "adler2"
+version = "2.0.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "320119579fcad9c21884f5c4861d16174d0e06250625266f50fe6898340abefa"
+
+[[package]]
+name = "ahash"
+version = "0.8.12"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "5a15f179cd60c4584b8a8c596927aadc462e27f2ca70c04e0071964a73ba7a75"
+dependencies = [
+ "cfg-if 1.0.4",
+ "getrandom 0.3.4",
+ "once_cell",
+ "serde",
+ "version_check",
+ "zerocopy",
+]
+
+[[package]]
+name = "aho-corasick"
+version = "1.1.4"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "ddd31a130427c27518df266943a5308ed92d4b226cc639f5a8f1002816174301"
+dependencies = [
+ "memchr",
+]
+
+[[package]]
+name = "aligned"
+version = "0.4.3"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "ee4508988c62edf04abd8d92897fca0c2995d907ce1dfeaf369dac3716a40685"
+dependencies = [
+ "as-slice",
+]
+
+[[package]]
+name = "aligned-vec"
+version = "0.6.4"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "dc890384c8602f339876ded803c97ad529f3842aba97f6392b3dba0dd171769b"
+dependencies = [
+ "equator",
+]
+
+[[package]]
+name = "alloca"
+version = "0.4.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "e5a7d05ea6aea7e9e64d25b9156ba2fee3fdd659e34e41063cd2fc7cd020d7f4"
+dependencies = [
+ "cc",
+]
+
+[[package]]
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+version = "0.2.21"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "683d7910e743518b0e34f1186f92494becacb047c7b6bf616c96772180fef923"
+
+[[package]]
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+version = "0.11.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "812947049edcd670a82cd5c73c3661d2e58468577ba8489de58e1a73c04cbd5d"
+dependencies = [
+ "alsa-sys",
+ "bitflags 2.11.1",
+ "cfg-if 1.0.4",
+ "libc",
+]
+
+[[package]]
+name = "alsa-sys"
+version = "0.4.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "ad7569085a265dd3f607ebecce7458eaab2132a84393534c95b18dcbc3f31e04"
+dependencies = [
+ "libc",
+ "pkg-config",
+]
+
+[[package]]
+name = "anes"
+version = "0.1.6"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "4b46cbb362ab8752921c97e041f5e366ee6297bd428a31275b9fcf1e380f7299"
+
+[[package]]
+name = "anstream"
+version = "1.0.0"
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+checksum = "b97154e67e32c85465826e8bcc1c59429aaaf107c1e4a9e53c8d8ccd5eff88d0"
+
+[[package]]
+name = "zerotrie"
+version = "0.2.4"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "0f9152d31db0792fa83f70fb2f83148effb5c1f5b8c7686c3459e361d9bc20bf"
+dependencies = [
+ "displaydoc",
+ "yoke",
+ "zerofrom",
+]
+
+[[package]]
+name = "zerovec"
+version = "0.11.6"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "90f911cbc359ab6af17377d242225f4d75119aec87ea711a880987b18cd7b239"
+dependencies = [
+ "yoke",
+ "zerofrom",
+ "zerovec-derive",
+]
+
+[[package]]
+name = "zerovec-derive"
+version = "0.11.3"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "625dc425cab0dca6dc3c3319506e6593dcb08a9f387ea3b284dbd52a92c40555"
+dependencies = [
+ "proc-macro2",
+ "quote",
+ "syn",
+]
+
+[[package]]
+name = "zip"
+version = "6.0.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "eb2a05c7c36fde6c09b08576c9f7fb4cda705990f73b58fe011abf7dfb24168b"
+dependencies = [
+ "arbitrary",
+ "crc32fast",
+ "flate2",
+ "indexmap",
+ "memchr",
+ "zopfli",
+]
+
+[[package]]
+name = "zlib-rs"
+version = "0.6.3"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "3be3d40e40a133f9c916ee3f9f4fa2d9d63435b5fbe1bfc6d9dae0aa0ada1513"
+
+[[package]]
+name = "zmij"
+version = "1.0.21"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "b8848ee67ecc8aedbaf3e4122217aff892639231befc6a1b58d29fff4c2cabaa"
+
+[[package]]
+name = "zopfli"
+version = "0.8.3"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "f05cd8797d63865425ff89b5c4a48804f35ba0ce8d125800027ad6017d2b5249"
+dependencies = [
+ "bumpalo",
+ "crc32fast",
+ "log",
+ "simd-adler32",
+]
+
+[[package]]
+name = "zune-core"
+version = "0.5.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "cb8a0807f7c01457d0379ba880ba6322660448ddebc890ce29bb64da71fb40f9"
+
+[[package]]
+name = "zune-inflate"
+version = "0.2.54"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "73ab332fe2f6680068f3582b16a24f90ad7096d5d39b974d1c0aff0125116f02"
+dependencies = [
+ "simd-adler32",
+]
+
+[[package]]
+name = "zune-jpeg"
+version = "0.5.15"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "27bc9d5b815bc103f142aa054f561d9187d191692ec7c2d1e2b4737f8dbd7296"
+dependencies = [
+ "zune-core",
+]
diff --git a/Cargo.toml b/Cargo.toml
index 81b9e48164..95d87f6ac9 100644
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -125,7 +125,6 @@ anstyle-query = "1.0.0"
 anyhow = "1.0.43"
 anymap3 = "1.0"
 approx = "0.5"
-atty = "0.2.14"
 bit-set = "0.10.0"
 boow = "0.1.3"
 box_drawing = "0.1.2"
@@ -206,37 +205,36 @@ smallvec = "1.6.1"
 string-interner = "0.20"
 tar = "0.4.37"
 tempfile = "3.8"
-tensorflow = "0.21.0"
 tflitec = { git = "https://github.com/kali/tflitec-rs.git", rev="9ceb838" }
 time = "0.3.23"
 tokenizers = "0.23"
 unicode-normalization = "0.1.19"
 walkdir = "2.3.2"
 zerofrom = "0.1.5"
-tract-api = { version = "=0.23.0-dev.4", path = 'api' }
-tract-core = { version = "0.23.0-pre", path = 'core' }
-tract-cuda = { version = "0.23.0-pre", path = 'cuda', default-features = false }
-tract-data = { version = "0.23.0-pre", path = 'data' }
-tract-extra = { version = "0.23.0-pre", path = 'extra' }
-tract-gpu = { version = "0.23.0-pre", path = 'gpu' }
-tract-hir = { version = "0.23.0-pre", path = 'hir' }
-tract-libcli = { version = "0.23.0-pre", path = 'libcli' }
-tract-linalg = { version = "0.23.0-pre", path = 'linalg' }
-tract-metal = { version = "0.23.0-pre", path = 'metal' }
-tract-nnef-resources = { version = "0.23.0-pre", path = 'nnef/nnef-resources' }
-tract-nnef = { version = "0.23.0-pre", path = 'nnef' }
-tract-onnx-opl = { version = "0.23.0-pre", path = 'onnx-opl' }
-tract-onnx = { version = "0.23.0-pre", path = 'onnx' }
-tract-pulse-opl = { version = "0.23.0-pre", path = 'pulse-opl' }
-tract-pulse = { version = "0.23.0-pre", path = 'pulse' }
-tract-tensorflow = { version = "0.23.0-pre", path = 'tensorflow' }
-tract-tflite = { version = "0.23.0-pre", path = 'tflite' }
-tract-transformers = { version = "0.23.0-pre", path = 'transformers' }
-tract = { version = "0.23.0-pre", path = 'api/rs' }
-tract-proxy-sys = { version = "0.23.0-pre", path = 'api/proxy/sys' }
-tract-cli = { version = "0.23.0-pre", path = 'cli' }
-tract-ffi = { version = "0.23.0-pre" }
-tract-proxy = { version = "0.23.0-pre" }
+tract-api = { version = "0.23.1-pre", path = 'api' }
+tract-core = { version = "0.23.1-pre", path = 'core' }
+tract-cuda = { version = "0.23.1-pre", path = 'cuda', default-features = false }
+tract-data = { version = "0.23.1-pre", path = 'data' }
+tract-extra = { version = "0.23.1-pre", path = 'extra' }
+tract-gpu = { version = "0.23.1-pre", path = 'gpu' }
+tract-hir = { version = "0.23.1-pre", path = 'hir' }
+tract-libcli = { version = "0.23.1-pre", path = 'libcli' }
+tract-linalg = { version = "0.23.1-pre", path = 'linalg' }
+tract-metal = { version = "0.23.1-pre", path = 'metal' }
+tract-nnef-resources = { version = "0.23.1-pre", path = 'nnef/nnef-resources' }
+tract-nnef = { version = "0.23.1-pre", path = 'nnef' }
+tract-onnx-opl = { version = "0.23.1-pre", path = 'onnx-opl' }
+tract-onnx = { version = "0.23.1-pre", path = 'onnx' }
+tract-pulse-opl = { version = "0.23.1-pre", path = 'pulse-opl' }
+tract-pulse = { version = "0.23.1-pre", path = 'pulse' }
+tract-tensorflow = { version = "0.23.1-pre", path = 'tensorflow' }
+tract-tflite = { version = "0.23.1-pre", path = 'tflite' }
+tract-transformers = { version = "0.23.1-pre", path = 'transformers' }
+tract = { version = "0.23.1-pre", path = 'api/rs' }
+tract-proxy-sys = { version = "0.23.1-pre", path = 'api/proxy/sys' }
+tract-cli = { version = "0.23.1-pre", path = 'cli' }
+tract-ffi = { version = "0.23.1-pre" }
+tract-proxy = { version = "0.23.1-pre" }
 
 
 [profile.opt-no-lto]
diff --git a/api/Cargo.toml b/api/Cargo.toml
index d4a868f273..a7c0b1b77e 100644
--- a/api/Cargo.toml
+++ b/api/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-api"
-version = "0.23.0-dev.4"
+version = "0.23.1-pre"
 license = "MIT OR Apache-2.0"
 authors = ["Mathieu Poumeyrol <kali@zoy.org>"]
 description = "Tiny, no-nonsense, self contained, TensorFlow and ONNX inference"
diff --git a/api/ffi/Cargo.toml b/api/ffi/Cargo.toml
index f65b5b3698..6f7ce13bb6 100644
--- a/api/ffi/Cargo.toml
+++ b/api/ffi/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-ffi"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 license = "MIT OR Apache-2.0"
 authors = ["Mathieu Poumeyrol <kali@zoy.org>"]
 description = "Tiny, no-nonsense, self contained, neural network inference"
diff --git a/api/proxy/Cargo.toml b/api/proxy/Cargo.toml
index f7300b3415..d3f6cca395 100644
--- a/api/proxy/Cargo.toml
+++ b/api/proxy/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-proxy"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 license = "MIT OR Apache-2.0"
 authors = ["Mathieu Poumeyrol <kali@zoy.org>"]
 description = "Tiny, no-nonsense, self contained, TensorFlow and ONNX inference"
diff --git a/api/proxy/sys/Cargo.toml b/api/proxy/sys/Cargo.toml
index f82a5a9d75..4aea3fad78 100644
--- a/api/proxy/sys/Cargo.toml
+++ b/api/proxy/sys/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-proxy-sys"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 license = "MIT OR Apache-2.0"
 authors = ["Mathieu Poumeyrol <kali@zoy.org>"]
 description = "Tiny, no-nonsense, self contained, TensorFlow and ONNX inference"
diff --git a/api/py/pyproject.toml b/api/py/pyproject.toml
index 7043dd3362..53a36e0545 100644
--- a/api/py/pyproject.toml
+++ b/api/py/pyproject.toml
@@ -21,13 +21,27 @@ cargo --version || (curl https://sh.rustup.rs -sSf | sh -s -- -y --profile minim
 . $HOME/.cargo/env
 rustup toolchain add stable
 rustup default stable)
-[ -e $HOME/.local/bin/sccache ] || ./.travis/setup-sccache.sh ]
+[ -e $HOME/.local/bin/sccache ] || ./.travis/setup-sccache.sh ]
+# cargo-auditable embeds the resolved Rust dep graph into the .so the
+# wheel ships.  setuptools_rust honours $CARGO (build.py:97); point it
+# at a shim that prefixes `auditable` for build/rustc.
+cargo install --locked cargo-auditable --version 0.7.0
+mkdir -p "$HOME/cargo-shim"
+cat > "$HOME/cargo-shim/cargo" <<'EOSHIM'
+#!/usr/bin/env bash
+# `cargo auditable <anything>` forwards transparently to cargo, so an
+# unconditional prefix is safe for the version/metadata/build calls
+# setuptools_rust makes.
+exec cargo auditable "$@"
+EOSHIM
+chmod +x "$HOME/cargo-shim/cargo"
 """
 environment = """
 PATH=$HOME/.local/bin:$HOME/.cargo/bin:$PATH
 SCCACHE_DIR=$HOME/.cache/sccache
 SCCACHE_CACHE_SIZE=2G
 RUSTC_WRAPPER=sccache
+CARGO=$HOME/cargo-shim/cargo
 """
 
 [tool.cibuildwheel.macos]
@@ -36,10 +50,27 @@ skip = "pp* cp???t-*"
 before-build = """
 uv pip install --system "numpy>=2,<3" --config-settings=setup-args="-Dallow-noblas=true"
 rustup target add aarch64-apple-darwin
-[ -e $HOME/.local/bin/sccache ] || ./.travis/setup-sccache.sh ]
+[ -e $HOME/.local/bin/sccache ] || ./.travis/setup-sccache.sh ]
+# Same cargo-auditable shim as Linux (see comment there).
+cargo install --locked cargo-auditable --version 0.7.0
+mkdir -p "$HOME/cargo-shim"
+cat > "$HOME/cargo-shim/cargo" <<'EOSHIM'
+#!/usr/bin/env bash
+# `cargo auditable <anything>` forwards transparently to cargo, so an
+# unconditional prefix is safe for the version/metadata/build calls
+# setuptools_rust makes.
+exec cargo auditable "$@"
+EOSHIM
+chmod +x "$HOME/cargo-shim/cargo"
+"""
+environment = """
+CARGO=$HOME/cargo-shim/cargo
 """
 
 [tool.cibuildwheel.windows]
+# TODO: add a .cmd shim equivalent of the Linux/macOS bash shim above to
+# enable cargo-auditable here too.  Windows wheels currently ship without
+# the embedded Rust dep graph.
 before-build = """
 choco install mingw --version=8.1.0
 uv pip install --system "numpy==1.25.2"
diff --git a/api/py/tests/mobilenet_onnx_test.py b/api/py/tests/mobilenet_onnx_test.py
index 507c59af11..ba5451df25 100644
--- a/api/py/tests/mobilenet_onnx_test.py
+++ b/api/py/tests/mobilenet_onnx_test.py
@@ -99,7 +99,7 @@ def test_concretize():
     typed = model.into_model()
     assert str(typed.input_fact(0)) == "B,3,224,224,f32"
     assert str(typed.output_fact(0)) == "B,1000,f32"
-    typed.transform(tract.ConcretizeSymbols({"B": 1}))
+    typed.transform(tract.SetSymbols({"B": 1}))
     assert str(typed.input_fact(0)) == "1,3,224,224,f32"
     assert str(typed.output_fact(0)) == "1,1000,f32"
 
@@ -108,7 +108,7 @@ def test_concretize_builder():
     model.set_input_fact(0, "B,3,224,224,f32")
     model.analyse()
     typed = model.into_model()
-    typed.transform(tract.ConcretizeSymbols().value("B", 1))
+    typed.transform(tract.SetSymbols().value("B", 1))
     assert str(typed.input_fact(0)) == "1,3,224,224,f32"
     assert str(typed.output_fact(0)) == "1,1000,f32"
 
@@ -117,7 +117,7 @@ def test_concretize_raw_string():
     model.set_input_fact(0, "B,3,224,224,f32")
     model.analyse()
     typed = model.into_model()
-    typed.transform('{"name":"concretize_symbols","values":{"B":1}}')
+    typed.transform('{"name":"set_symbols","values":{"B":1}}')
     assert str(typed.input_fact(0)) == "1,3,224,224,f32"
     assert str(typed.output_fact(0)) == "1,1000,f32"
 
diff --git a/api/py/tract/__init__.py b/api/py/tract/__init__.py
index 40c5166bf3..940bf4c639 100644
--- a/api/py/tract/__init__.py
+++ b/api/py/tract/__init__.py
@@ -49,7 +49,7 @@
 from .inference_model import InferenceModel
 from .runnable import Runnable
 from .runtime import Runtime, runtime_for_name
-from .transform import TransformSpec, ConcretizeSymbols, FloatPrecision, Pulse
+from .transform import TransformSpec, SetSymbols, FloatPrecision, Pulse
 from .nnef import Nnef
 from .onnx import Onnx
 
diff --git a/api/py/tract/model.py b/api/py/tract/model.py
index ead15407d4..a143715018 100644
--- a/api/py/tract/model.py
+++ b/api/py/tract/model.py
@@ -109,7 +109,7 @@ def transform(self, transform: Union[str, "TransformSpec"]) -> None:
 
         - a plain string name (e.g. ``"f32_to_f16"``)
         - a JSON string with a ``"name"`` key and parameters
-        - a :class:`TransformSpec` subclass such as :class:`ConcretizeSymbols`
+        - a :class:`TransformSpec` subclass such as :class:`SetSymbols`
           or :class:`Pulse`
         """
         self._valid()
diff --git a/api/py/tract/transform.py b/api/py/tract/transform.py
index 2926040bc4..35299d70b6 100644
--- a/api/py/tract/transform.py
+++ b/api/py/tract/transform.py
@@ -18,26 +18,28 @@ def to_json(self) -> str:
         ...
 
 
-class ConcretizeSymbols(TransformSpec):
-    """Replace symbolic dimensions with concrete integer values.
+class SetSymbols(TransformSpec):
+    """Bind symbolic dimensions to concrete integer values (or TDim expressions).
 
     Example::
 
-        model.transform(ConcretizeSymbols({"B": 1}))
+        model.transform(SetSymbols({"B": 1}))
         # or with builder pattern:
-        model.transform(ConcretizeSymbols().value("B", 1))
+        model.transform(SetSymbols().value("B", 1))
+        # for symbolic TDim expressions, pass a string:
+        model.transform(SetSymbols().value("B", "2*S"))
     """
 
-    def __init__(self, values: Optional[Dict[str, int]] = None):
-        self._values: Dict[str, int] = dict(values) if values else {}
+    def __init__(self, values: Optional[Dict[str, Union[int, str]]] = None):
+        self._values: Dict[str, Union[int, str]] = dict(values) if values else {}
 
-    def value(self, symbol: str, val: int) -> "ConcretizeSymbols":
-        """Set a symbol to a concrete value. Returns self for chaining."""
+    def value(self, symbol: str, val: Union[int, str]) -> "SetSymbols":
+        """Bind a symbol to an int or TDim expression string. Returns self for chaining."""
         self._values[symbol] = val
         return self
 
     def to_json(self) -> str:
-        return json.dumps({"name": "concretize_symbols", "values": self._values})
+        return json.dumps({"name": "set_symbols", "values": self._values})
 
 
 class Pulse(TransformSpec):
diff --git a/api/rs/Cargo.toml b/api/rs/Cargo.toml
index 457a943486..ca1014377f 100644
--- a/api/rs/Cargo.toml
+++ b/api/rs/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 license = "MIT OR Apache-2.0"
 authors = ["Mathieu Poumeyrol <kali@zoy.org>"]
 description = "Tiny, no-nonsense, self contained, TensorFlow and ONNX inference"
diff --git a/deny.toml b/api/rs/deny.toml
similarity index 97%
rename from deny.toml
rename to api/rs/deny.toml
index cf3ebfbef2..66aa54784f 100644
--- a/deny.toml
+++ b/api/rs/deny.toml
@@ -34,7 +34,6 @@ deny = [
 # Skip some multiple-versions checks, until they can be fixed.
 skip = [
     { name = "hashbrown", version="<0.17" },
-    { name = "foldhash", version="<0.2" },
     { name = "cpufeatures", version="<0.3" },
     { name = "cfg-if", version="<1" },
     { name = "getrandom", version="<0.4" },
diff --git a/api/rs/src/lib.rs b/api/rs/src/lib.rs
index 636829d586..265f01e939 100644
--- a/api/rs/src/lib.rs
+++ b/api/rs/src/lib.rs
@@ -39,7 +39,7 @@ pub mod prelude {
 
     // User-facing API types
     pub use tract_api::{
-        ConcretizeSymbols, Datum, DatumType, FloatPrecision, Pulse, TransformSpec, tensor,
+        Datum, DatumType, FloatPrecision, Pulse, SetSymbols, TransformSpec, tensor,
     };
 
     // Traits needed for method resolution — hidden from namespace
diff --git a/api/src/lib.rs b/api/src/lib.rs
index df3a35d6fc..4617529ee8 100644
--- a/api/src/lib.rs
+++ b/api/src/lib.rs
@@ -7,7 +7,7 @@ use std::path::Path;
 pub mod macros;
 pub mod transform;
 
-pub use transform::{ConcretizeSymbols, FloatPrecision, Pulse, TransformConfig, TransformSpec};
+pub use transform::{FloatPrecision, Pulse, SetSymbols, TransformConfig, TransformSpec};
 
 /// an implementation of tract's NNEF framework object
 ///
diff --git a/api/src/transform.rs b/api/src/transform.rs
index 91d4d09fd3..3f11359b0b 100644
--- a/api/src/transform.rs
+++ b/api/src/transform.rs
@@ -74,32 +74,60 @@ macro_rules! transform_config {
     };
 }
 
-/// Typed config for the `concretize_symbols` transform.
+/// Typed config for the `set_symbols` transform.
 ///
-/// Replaces symbolic dimensions with concrete integer values.
+/// Binds symbolic dimensions to concrete integers (or `TDim` expressions
+/// via [`Self::expr`]).
 ///
 /// # Example
 /// ```ignore
-/// model.transform(ConcretizeSymbols::new().value("B", 1))?;
+/// model.transform(SetSymbols::new().value("B", 1).value("T", 16))?;
 /// ```
 #[derive(Debug, Clone, Default, serde::Serialize)]
-pub struct ConcretizeSymbols {
-    values: HashMap<String, i64>,
+pub struct SetSymbols {
+    #[serde(serialize_with = "serialize_values")]
+    values: HashMap<String, SetSymbolValue>,
 }
 
-impl ConcretizeSymbols {
+#[derive(Debug, Clone, serde::Serialize)]
+#[serde(untagged)]
+enum SetSymbolValue {
+    Int(i64),
+    Expr(String),
+}
+
+fn serialize_values<S: serde::Serializer>(
+    values: &HashMap<String, SetSymbolValue>,
+    s: S,
+) -> Result<S::Ok, S::Error> {
+    use serde::ser::SerializeMap;
+    let mut map = s.serialize_map(Some(values.len()))?;
+    for (k, v) in values {
+        map.serialize_entry(k, v)?;
+    }
+    map.end()
+}
+
+impl SetSymbols {
     pub fn new() -> Self {
         Self::default()
     }
 
-    /// Set a symbol to a concrete value.
+    /// Bind a symbol to a concrete integer value.
     pub fn value(mut self, symbol: impl Into<String>, val: i64) -> Self {
-        self.values.insert(symbol.into(), val);
+        self.values.insert(symbol.into(), SetSymbolValue::Int(val));
+        self
+    }
+
+    /// Bind a symbol to a `TDim` expression (e.g. `"2*S"`) parsed against
+    /// the model's symbol scope at transform time.
+    pub fn expr(mut self, symbol: impl Into<String>, expr: impl Into<String>) -> Self {
+        self.values.insert(symbol.into(), SetSymbolValue::Expr(expr.into()));
         self
     }
 }
 
-transform_config!(ConcretizeSymbols, "concretize_symbols");
+transform_config!(SetSymbols, "set_symbols");
 
 /// Typed config for the `pulse` transform.
 ///
diff --git a/api/tests/mobilenet/mod.rs b/api/tests/mobilenet/mod.rs
index 2487a2c999..62e3ccc420 100644
--- a/api/tests/mobilenet/mod.rs
+++ b/api/tests/mobilenet/mod.rs
@@ -123,7 +123,7 @@ fn test_concretize() -> anyhow::Result<()> {
     let mut typed = model.into_model()?;
     assert_eq!(typed.input_fact(0)?.to_string(), "B,3,224,224,f32");
     assert_eq!(typed.output_fact(0)?.to_string(), "B,1000,f32");
-    typed.transform(ConcretizeSymbols::new().value("B", 1))?;
+    typed.transform(SetSymbols::new().value("B", 1))?;
     assert_eq!(typed.input_fact(0)?.to_string(), "1,3,224,224,f32");
     assert_eq!(typed.output_fact(0)?.to_string(), "1,1000,f32");
     Ok(())
@@ -136,7 +136,7 @@ fn test_concretize_raw_string() -> anyhow::Result<()> {
     model.set_input_fact(0, "B,3,224,224,f32")?;
     model.analyse()?;
     let mut typed = model.into_model()?;
-    typed.transform(r#"{"name":"concretize_symbols","values":{"B":1}}"#)?;
+    typed.transform(r#"{"name":"set_symbols","values":{"B":1}}"#)?;
     assert_eq!(typed.input_fact(0)?.to_string(), "1,3,224,224,f32");
     assert_eq!(typed.output_fact(0)?.to_string(), "1,1000,f32");
     Ok(())
diff --git a/cli/Cargo.toml b/cli/Cargo.toml
index e17edb2504..0673673594 100644
--- a/cli/Cargo.toml
+++ b/cli/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-cli"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 authors = [
   "Romain Liautaud <romain.liautaud@snips.ai>",
   "Mathieu Poumeyrol <kali@zoy.org>",
@@ -22,7 +22,6 @@ path = "src/main.rs"
 maintenance = { status = "actively-developed" }
 
 [dependencies]
-atty.workspace = true
 box_drawing.workspace = true
 clap.workspace = true
 erased-serde.workspace = true
@@ -74,8 +73,8 @@ float-ord.workspace = true
 tract-metal.workspace = true
 
 [target.'cfg(any(target_os = "linux", target_os = "windows"))'.dependencies]
-cudarc.workspace = true
-tract-cuda = { workspace = true, default-features = false }
+cudarc = { workspace = true, optional = true }
+tract-cuda = { workspace = true, optional = true }
 
 [features]
 default = [
@@ -96,23 +95,29 @@ pulse = ["tract-pulse", "tract-pulse-opl"]
 tf = ["tract-tensorflow", "tract-libcli/hir"]
 tflite = ["tract-tflite"]
 transformers = ["tract-transformers", "tract-libcli/transformers"]
-conform = ["tract-tensorflow/conform"]
 multithread-mm = ["tract-linalg/multithread-mm"]
 
+# Marker feature implicitly enabled by every cuda-XXXXX selector below.
+# Use to gate cudarc-specific code paths in tract-cli. Not meant to be
+# enabled directly — always pick a concrete cuda-XXXXX so cudarc has an
+# API version to bind against.
+cuda = []
+
 # CUDA driver-API selectors (linux/windows targets only). Picking one binds
 # cudarc against the matching CUDA enum/struct layout; the resulting binary
 # runs on any driver whose API is >= the chosen one. Exactly one must be
 # active. The default pulls cuda-13000 in; cross-compiles aimed at older
-# drivers (e.g. aarch64 with CUDA 12) override with `--no-default-features`.
-cuda-12000 = ["tract-cuda/cuda-12000"]
-cuda-12010 = ["tract-cuda/cuda-12010"]
-cuda-12020 = ["tract-cuda/cuda-12020"]
-cuda-12030 = ["tract-cuda/cuda-12030"]
-cuda-12040 = ["tract-cuda/cuda-12040"]
-cuda-12050 = ["tract-cuda/cuda-12050"]
-cuda-12060 = ["tract-cuda/cuda-12060"]
-cuda-12080 = ["tract-cuda/cuda-12080"]
-cuda-12090 = ["tract-cuda/cuda-12090"]
-cuda-13000 = ["tract-cuda/cuda-13000"]
-cuda-13010 = ["tract-cuda/cuda-13010"]
-cuda-13020 = ["tract-cuda/cuda-13020"]
+# drivers (e.g. aarch64 with CUDA 12) override with `--no-default-features`
+# plus an explicit cuda-12XXX.
+cuda-12000 = ["cuda", "dep:cudarc", "dep:tract-cuda", "tract-libcli/cuda", "tract-cuda/cuda-12000"]
+cuda-12010 = ["cuda", "dep:cudarc", "dep:tract-cuda", "tract-libcli/cuda", "tract-cuda/cuda-12010"]
+cuda-12020 = ["cuda", "dep:cudarc", "dep:tract-cuda", "tract-libcli/cuda", "tract-cuda/cuda-12020"]
+cuda-12030 = ["cuda", "dep:cudarc", "dep:tract-cuda", "tract-libcli/cuda", "tract-cuda/cuda-12030"]
+cuda-12040 = ["cuda", "dep:cudarc", "dep:tract-cuda", "tract-libcli/cuda", "tract-cuda/cuda-12040"]
+cuda-12050 = ["cuda", "dep:cudarc", "dep:tract-cuda", "tract-libcli/cuda", "tract-cuda/cuda-12050"]
+cuda-12060 = ["cuda", "dep:cudarc", "dep:tract-cuda", "tract-libcli/cuda", "tract-cuda/cuda-12060"]
+cuda-12080 = ["cuda", "dep:cudarc", "dep:tract-cuda", "tract-libcli/cuda", "tract-cuda/cuda-12080"]
+cuda-12090 = ["cuda", "dep:cudarc", "dep:tract-cuda", "tract-libcli/cuda", "tract-cuda/cuda-12090"]
+cuda-13000 = ["cuda", "dep:cudarc", "dep:tract-cuda", "tract-libcli/cuda", "tract-cuda/cuda-13000"]
+cuda-13010 = ["cuda", "dep:cudarc", "dep:tract-cuda", "tract-libcli/cuda", "tract-cuda/cuda-13010"]
+cuda-13020 = ["cuda", "dep:cudarc", "dep:tract-cuda", "tract-libcli/cuda", "tract-cuda/cuda-13020"]
diff --git a/cli/deny.toml b/cli/deny.toml
new file mode 100644
index 0000000000..bee6142bb0
--- /dev/null
+++ b/cli/deny.toml
@@ -0,0 +1,53 @@
+
+# add whatever else we support.
+[graph]
+targets = [
+    { triple = "x86_64-unknown-linux-gnu" },
+    { triple = "x86_64-unknown-linux-musl" },
+    { triple = "x86_64-apple-darwin" },
+    { triple = "x86_64-pc-windows-msvc" },
+    { triple = "aarch64-linux-android" },
+    { triple = "aarch64-unknown-linux-gnu" },
+    { triple = "aarch64-unknown-linux-musl" },
+    { triple = "aarch64-apple-ios" },
+    { triple = "aarch64-apple-darwin" },
+    { triple = "armv7-unknown-linux-gnueabihf" },
+    { triple = "armv7-unknown-linux-musleabi" },
+    { triple = "arm-unknown-linux-gnueabihf" },
+    { triple = "wasm32-unknown-unknown" },
+]
+
+[advisories]
+git-fetch-with-cli = true
+yanked = "deny"
+ignore = [
+    "RUSTSEC-2024-0436", # paste unmaintained — transitive dep from metal, tokenizers, rav1e
+]
+
+[bans]
+multiple-versions = "allow"
+wildcards = "allow"
+deny = [
+    # List crates we don't want in our dependency tree here.
+]
+
+[sources]
+# trusted git sources.
+allow-git = [
+    "https://github.com/rustformers/llm.git",
+]
+
+[licenses]
+allow = [
+    "Apache-2.0",                     # https://tldrlegal.com/license/apache-license-2.0-(apache-2.0)
+    "MIT",                            # https://tldrlegal.com/license/mit-license
+    "Unicode-3.0",                    # https://spdx.org/licenses/Unicode-3.0.html
+    "Zlib",                           # https://tldrlegal.com/license/zlib-libpng-license
+    "ISC",                            # https://tldrlegal.com/license/isc-license
+    "MPL-2.0",                        # https://tldrlegal.com/license/mozilla-public-license-2.0-(mpl-2)
+    "BSD-3-Clause",                   # https://www.tldrlegal.com/license/bsd-3-clause-license-revised
+    "CDLA-Permissive-2.0",            # https://cdla.dev/permissive-2-0/
+]
+
+clarify = [
+]
diff --git a/cli/src/bench.rs b/cli/src/bench.rs
index 445e2ab00f..630679d989 100644
--- a/cli/src/bench.rs
+++ b/cli/src/bench.rs
@@ -33,7 +33,7 @@ pub fn handle(
     limits.warmup(&params.req_runnable()?, &inputs)?;
 
     let (iters, dur) = {
-        #[cfg(any(target_os = "linux", target_os = "windows"))]
+        #[cfg(all(any(target_os = "linux", target_os = "windows"), feature = "cuda"))]
         let _profiler =
             sub_matches.get_flag("cuda-gpu-trace").then(cudarc::driver::safe::Profiler::new);
         limits.bench(&params.req_runnable()?, &inputs)?
diff --git a/cli/src/compare.rs b/cli/src/compare.rs
index b16650f24c..a2785cc4d9 100644
--- a/cli/src/compare.rs
+++ b/cli/src/compare.rs
@@ -26,7 +26,6 @@ pub fn handle(
     }
 
     let cumulative = sub_matches.get_flag("cumulative");
-    let resilent = sub_matches.get_flag("resilient");
     if sub_matches.get_one::<String>("stage").is_some() {
         // --with is by pipeline and put in params
         return handle_reference_stage(cumulative, params, &output_params, &run_params);
@@ -38,100 +37,9 @@ pub fn handle(
     if let Some(pbdir) = sub_matches.get_one::<String>("pbdir") {
         return handle_pbdir(cumulative, pbdir, params, &output_params, &run_params);
     }
-    if sub_matches.get_flag("tf") {
-        return handle_tensorflow(cumulative, resilent, params, &output_params, &run_params);
-    }
     bail!("No comparison target found")
 }
 
-#[cfg(not(feature = "conform"))]
-pub fn handle_tensorflow(
-    _cumulative: bool,
-    _resilient: bool,
-    _params: &mut Parameters,
-    _output_params: &DisplayParams,
-    _run_params: &RunParams,
-) -> TractResult<()> {
-    bail!("`tf` feature is required for this to work");
-}
-
-#[cfg(feature = "conform")]
-pub fn handle_tensorflow(
-    cumulative: bool,
-    resilient: bool,
-    params: &mut Parameters,
-    output_params: &DisplayParams,
-    run_params: &RunParams,
-) -> TractResult<()> {
-    let tract = &params.tract_model;
-    let mut tf = params.tf_model.take().unwrap();
-    // First generate random values for the inputs.
-    let input_facts = tract
-        .input_outlets()
-        .iter()
-        .map(|&i| tract.outlet_typedfact(i))
-        .collect::<TractResult<Vec<_>>>()?;
-    let generated = crate::tensor::make_inputs(&*input_facts)?;
-
-    // Execute the model on tensorflow first.
-    info!("Running the model on tensorflow.");
-    trace!("Inject inputs in tensorflow graph.");
-    let pairs: Vec<_> = tract
-        .input_outlets()
-        .iter()
-        .map(|s| &*tract.node_name(s.node))
-        .zip(generated.iter().cloned())
-        .collect();
-
-    trace!("Execute the model on tensorflow.");
-    let eval_order = tract.eval_order()?;
-
-    let mut wanted_outputs: Vec<&str> = eval_order
-        .iter()
-        .filter(|&n| !tract.input_outlets().contains(&OutletId::new(*n, 0)))
-        .map(|&n| tract.node_name(n))
-        .collect();
-
-    for o in tract.output_outlets() {
-        let name = &*tract.node_name(o.node);
-        if !wanted_outputs.contains(&name) {
-            wanted_outputs.push(name);
-        }
-    }
-
-    let mut all_values: HashMap<String, Vec<TractResult<TValue>>> = HashMap::new();
-    if resilient {
-        for name in wanted_outputs {
-            all_values.insert(
-                name.to_string(),
-                vec![
-                    tf.run(pairs.clone(), &name)
-                        .map(|t| Arc::new(t[0].clone().into()))
-                        .map_err(|e| e.into()),
-                ],
-            );
-        }
-    } else {
-        tf.run_get_many(pairs, wanted_outputs)?.into_iter().for_each(|(k, v)| {
-            all_values.insert(k.to_string(), vec![Ok(v[0].clone().into())]);
-        });
-    };
-
-    for (ix, input) in tract.input_outlets().iter().enumerate() {
-        let name = tract.node_name(input.node);
-        all_values.insert(name.to_string(), vec![Ok(generated[ix].clone().into_arc_tensor())]);
-    }
-    dispatch_model_no_pulse!(params.tract_model, |m| compare(
-        cumulative,
-        m,
-        &all_values,
-        &params,
-        &output_params,
-        run_params,
-        ("tract", "tf"),
-    ))
-}
-
 pub fn handle_npz(
     cumulative: bool,
     npz: &str,
@@ -516,8 +424,7 @@ pub fn handle_stream(
     }
 
     // Concretize the reference model and delegate to compare()
-    let concrete_ref =
-        Arc::new(reference.clone().substitute_symbols(&concrete_sym_values.to_dim_map())?);
+    let concrete_ref = Arc::new(reference.clone().set_symbols(&concrete_sym_values.to_dim_map())?);
     compare(
         false,
         &concrete_ref,
diff --git a/cli/src/dump.rs b/cli/src/dump.rs
index 03273f05fe..2fd3acc539 100644
--- a/cli/src/dump.rs
+++ b/cli/src/dump.rs
@@ -11,7 +11,7 @@ use tract_core::ops::matmul::optimized::{OptMatMul, ProtoFusedSpec};
 use tract_core::ops::matmul::pack::DynPackedExoticFact;
 use tract_core::ops::scan::OptScan;
 #[allow(unused_imports)]
-#[cfg(any(target_os = "linux", target_os = "windows"))]
+#[cfg(all(any(target_os = "linux", target_os = "windows"), feature = "cuda"))]
 use tract_cuda::utils::ensure_cuda_runtime_dependencies;
 use tract_hir::internal::*;
 use tract_itertools::Itertools;
@@ -146,17 +146,17 @@ pub fn handle(
 
             #[cfg(not(any(target_os = "macos", target_os = "ios")))]
             {
-                #[cfg(any(target_os = "linux", target_os = "windows"))]
+                #[cfg(all(any(target_os = "linux", target_os = "windows"), feature = "cuda"))]
                 ensure_cuda_runtime_dependencies("GPU profiling called on non-GPU device")?;
             }
 
-            #[cfg(any(target_os = "linux", target_os = "windows"))]
+            #[cfg(all(any(target_os = "linux", target_os = "windows"), feature = "cuda"))]
             let is_cuda = matches.get_flag("cuda");
-            #[cfg(not(any(target_os = "linux", target_os = "windows")))]
+            #[cfg(not(all(any(target_os = "linux", target_os = "windows"), feature = "cuda")))]
             let is_cuda = false;
 
             if is_cuda {
-                #[cfg(any(target_os = "linux", target_os = "windows"))]
+                #[cfg(all(any(target_os = "linux", target_os = "windows"), feature = "cuda"))]
                 tract_cuda::with_cuda_stream(|s| {
                     s.enable_profiling();
                     Ok(())
@@ -164,7 +164,7 @@ pub fn handle(
             }
 
             let before_node: Box<dyn Fn(usize)> = if is_cuda {
-                #[cfg(any(target_os = "linux", target_os = "windows"))]
+                #[cfg(all(any(target_os = "linux", target_os = "windows"), feature = "cuda"))]
                 {
                     Box::new(|node_id| {
                         tract_cuda::with_cuda_stream(|s| {
@@ -174,7 +174,10 @@ pub fn handle(
                         .ok();
                     })
                 }
-                #[cfg(not(any(target_os = "linux", target_os = "windows")))]
+                #[cfg(not(all(
+                    any(target_os = "linux", target_os = "windows"),
+                    feature = "cuda"
+                )))]
                 Box::new(|_| {})
             } else {
                 Box::new(|_| {})
@@ -186,7 +189,7 @@ pub fn handle(
                     &[(usize, String)],
                 ) -> TractResult<()>,
             > = if is_cuda {
-                #[cfg(any(target_os = "linux", target_os = "windows"))]
+                #[cfg(all(any(target_os = "linux", target_os = "windows"), feature = "cuda"))]
                 {
                     Box::new(|dg, prefix| {
                         tract_cuda::with_cuda_stream(|s| {
@@ -209,7 +212,10 @@ pub fn handle(
                         })
                     })
                 }
-                #[cfg(not(any(target_os = "linux", target_os = "windows")))]
+                #[cfg(not(all(
+                    any(target_os = "linux", target_os = "windows"),
+                    feature = "cuda"
+                )))]
                 Box::new(|_, _| Ok(()))
             } else {
                 Box::new(|_, _| Ok(()))
@@ -254,12 +260,20 @@ pub fn handle(
     }
 
     if sub_matches.contains_id("memory-arena") {
-        #[cfg(not(any(target_os = "macos", target_os = "ios")))]
+        #[cfg(all(any(target_os = "linux", target_os = "windows"), feature = "cuda"))]
         {
             ensure_cuda_runtime_dependencies(
                 "Memory arena is only enabled for MacOS / iOS devices or CUDA devices",
             )?;
         }
+        #[cfg(not(any(
+            target_os = "macos",
+            target_os = "ios",
+            all(any(target_os = "linux", target_os = "windows"), feature = "cuda")
+        )))]
+        bail!(
+            "Memory arena requires CUDA (Linux/Windows with cuda-* feature) or Metal (macOS/iOS)"
+        );
         crate::memory_arena::dump_metrics(
             &params.req_typed_model(),
             &plan_options_from_subcommand(sub_matches)?,
diff --git a/cli/src/hwbench.rs b/cli/src/hwbench.rs
index 13fe3a32e4..9725a3dd77 100644
--- a/cli/src/hwbench.rs
+++ b/cli/src/hwbench.rs
@@ -1,3 +1,5 @@
+use std::io::IsTerminal;
+
 use nu_ansi_term::Color::*;
 use tract_core::prelude::*;
 use tract_core::tract_data::itertools::Itertools;
@@ -107,7 +109,7 @@ fn mmm(dt: DatumType, m: usize, k: usize, n: usize) -> TractResult<()> {
                 pa.precursor().as_dt() == Some(dt) && pb.precursor().as_dt() == Some(dt)
             })
             .map(|(mmm, pix, pa, pb)| {
-                if atty::is(atty::Stream::Stderr) {
+                if std::io::stderr().is_terminal() {
                     eprint!("Benching {} ({pix})", mmm.name());
                 }
                 let a = pa.prepare_one(&a, 1, 0).unwrap();
@@ -132,7 +134,7 @@ fn mmm(dt: DatumType, m: usize, k: usize, n: usize) -> TractResult<()> {
                         .unwrap();
                     }
                 });
-                if atty::is(atty::Stream::Stderr) {
+                if std::io::stderr().is_terminal() {
                     eprint!("\x1B[2K\r"); // clear current line + CR
                 }
                 let flops = (m * k * n) as f64 / time;
diff --git a/cli/src/main.rs b/cli/src/main.rs
index bde9564ce1..215e8f30b1 100644
--- a/cli/src/main.rs
+++ b/cli/src/main.rs
@@ -186,9 +186,6 @@ fn main() -> TractResult<()> {
                 .value_parser(clap::builder::PossibleValuesParser::new(STAGES))
                 .help("Loading pipeline stage to compare with"),
         )
-        .arg(
-            Arg::new("tf").long("tf").action(ArgAction::SetTrue).help("Compare against tensorflow"),
-        )
         .arg(
             Arg::new("twice")
                 .long("twice")
@@ -210,7 +207,7 @@ fn main() -> TractResult<()> {
         )
         .group(
             ArgGroup::new("reference")
-                .args(&["npz", "pbdir", "stage", "tf", "twice", "stream"])
+                .args(&["npz", "pbdir", "stage", "twice", "stream"])
                 .required(true),
         )
         .arg(
@@ -559,7 +556,8 @@ fn run_options(command: clap::Command) -> clap::Command {
                 .long("set")
                 .action(clap::ArgAction::Append)
                 .number_of_values(1)
-                .help("Set a symbol value before running the model (--set S=12)"),
+                .help("Bind a symbol before running the model.  RHS is a TDim expression \
+                       reduced to i64 against symbols set so far (--set S=12, --set T=2*S)."),
         )
         .arg(
             Arg::new("input-from-nnef").long("input-from-nnef").num_args(1).help(
diff --git a/cli/src/params.rs b/cli/src/params.rs
index 345287b33f..09a434d9ec 100644
--- a/cli/src/params.rs
+++ b/cli/src/params.rs
@@ -134,13 +134,6 @@ pub struct Parameters {
     pub tract_model: Arc<dyn Model>,
     pub reference_model: Option<Arc<dyn Model>>,
 
-    #[cfg(feature = "conform")]
-    pub tf_model: Option<tract_tensorflow::conform::tf::Tensorflow>,
-
-    #[cfg(not(feature = "conform"))]
-    #[allow(dead_code)]
-    pub tf_model: (),
-
     pub tensors_values: TensorsValues,
     pub assertions: Assertions,
 
@@ -460,7 +453,7 @@ impl Parameters {
     /// `value` may be a plain integer or any TDim expression parseable
     /// against the model's symbol scope (e.g. `2*S` to rebase the
     /// streaming symbol onto a finer-grained chunk symbol before
-    /// pulsification).  Feeds straight into `model.substitute_symbols`.
+    /// pulsification).  Feeds straight into `model.set_symbols`.
     pub fn parse_set_subs(
         typed_model: &TypedModel,
         set: impl Iterator<Item = impl AsRef<str>>,
@@ -778,15 +771,15 @@ impl Parameters {
         }
 
         if let Some(set) = matches.get_many::<String>("set") {
-            // --set delegates to model.substitute_symbols with a
-            // Symbol → TDim map (same path the `concretize_symbols`
+            // --set delegates to model.set_symbols with a
+            // Symbol → TDim map (same path the `set_symbols`
             // model transform takes).  Values may be plain integers or
             // TDim expressions (e.g. `--set T=2*S` to rebase the
             // streaming symbol).  Const TDim tensors are rewritten
-            // through Const's own substitute_symbols hook.
+            // through Const's own set_symbols hook.
             let subs = Self::parse_set_subs(typed_model.as_ref().unwrap(), set)?;
             stage!("set", typed_model -> typed_model, move |m: TypedModel| {
-                m.substitute_symbols(&subs)
+                m.set_symbols(&subs)
             });
             stage!("set-declutter", typed_model -> typed_model, |mut m| {
                 let mut dec = tract_core::optim::Optimizer::declutter();
@@ -859,36 +852,17 @@ impl Parameters {
         info!("Model {filename:?} loaded");
         info_usage("model loaded", probe);
 
-        let (need_tensorflow_model, need_reference_model) = match matches.subcommand() {
+        let need_reference_model = match matches.subcommand() {
             Some(("compare", sm)) => {
                 if let Some(with) = sm.get_one::<String>("stage").map(String::as_str) {
-                    (false, Some(with))
+                    Some(with)
                 } else if sm.get_flag("stream") {
-                    (false, Some("declutter"))
+                    Some("declutter")
                 } else {
-                    (true, None)
-                }
-            }
-            _ => (false, None),
-        };
-
-        #[cfg(not(feature = "conform"))]
-        let tf_model = ();
-        #[cfg(feature = "conform")]
-        let tf_model = if need_tensorflow_model {
-            info!("Tensorflow version: {}", tract_tensorflow::conform::tf::version());
-            if matches.get_flag("determinize") {
-                if let SomeGraphDef::Tf(ref graph) = graph {
-                    let graph = graph.write_to_bytes().unwrap();
-                    Some(tract_tensorflow::conform::tf::for_slice(&graph)?)
-                } else {
-                    unreachable!()
+                    None
                 }
-            } else {
-                Some(tract_tensorflow::conform::tf::for_path(&filename)?)
             }
-        } else {
-            None
+            _ => None,
         };
 
         let need_proto = matches.get_flag("proto")
@@ -1062,7 +1036,6 @@ impl Parameters {
             runnable,
             tract_model,
             reference_model,
-            tf_model,
             tensors_values,
             assertions,
             machine_friendly: matches.get_flag("machine-friendly"),
diff --git a/cli/src/tensor.rs b/cli/src/tensor.rs
index f59ad6e745..f34826b3f6 100644
--- a/cli/src/tensor.rs
+++ b/cli/src/tensor.rs
@@ -72,13 +72,20 @@ pub fn run_params_from_subcommand(
     }
 
     if let Some(set) = sub_matches.get_many::<String>("set") {
+        // Right-hand side is a TDim expression (e.g. `--set T=2*S`).  Parse
+        // against the model's symbol scope, then reduce to `i64` with the
+        // symbols already set so far (CLI argument order matters when
+        // expressions reference other symbols).
+        let symbol_scope = params.tract_model.symbols();
         for set in set {
             let set = set.as_str();
-            let (sym, value) = set.split_once('=').context("--set expect S=12 form")?;
+            let (sym, value) = set.split_once('=').context("--set expects S=value form")?;
+            let dim = tract_core::internal::parse_tdim(symbol_scope, value)
+                .with_context(|| format!("--set: parsing TDim expression for {sym}={value}"))?;
+            let value: i64 = dim.eval_to_i64(&symbols).with_context(|| {
+                format!("--set {sym}={value}: resolving with current symbol values {symbols:?}")
+            })?;
             let sym = params.tract_model.get_or_intern_symbol(sym);
-            let value: i64 = value
-                .parse()
-                .with_context(|| format!("Can not parse symbol value in set {set}"))?;
             symbols.set(&sym, value);
         }
     }
diff --git a/core/Cargo.toml b/core/Cargo.toml
index f2a31c93b1..814043e490 100644
--- a/core/Cargo.toml
+++ b/core/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-core"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 license = "MIT OR Apache-2.0"
 authors = ["Mathieu Poumeyrol <kali@zoy.org>"]
 description = "Tiny, no-nonsense, self contained, TensorFlow and ONNX inference"
diff --git a/core/src/model/graph.rs b/core/src/model/graph.rs
index 90d460cbb5..7d28c2bd1c 100644
--- a/core/src/model/graph.rs
+++ b/core/src/model/graph.rs
@@ -172,6 +172,24 @@ where
         Ok(self)
     }
 
+    /// Set model inputs by node name — mirror of [`Self::select_outputs_by_name`].
+    /// Removed inputs become dangling Source nodes; declutter prunes them.
+    pub fn select_inputs_by_name(
+        &mut self,
+        inputs: impl IntoIterator<Item = impl AsRef<str>>,
+    ) -> TractResult<()> {
+        self.set_input_names(inputs)
+    }
+
+    /// Set model inputs by node name and return `self`.
+    pub fn with_inputs_by_name(
+        mut self,
+        inputs: impl IntoIterator<Item = impl AsRef<str>>,
+    ) -> TractResult<Self> {
+        self.select_inputs_by_name(inputs)?;
+        Ok(self)
+    }
+
     /// Get the `ix`-th input tensor type information.
     pub fn input_fact(&self, ix: usize) -> TractResult<&F> {
         let input = self.input_outlets()?[ix];
diff --git a/core/src/model/typed.rs b/core/src/model/typed.rs
index ea6b2c0fe1..64e730ee66 100644
--- a/core/src/model/typed.rs
+++ b/core/src/model/typed.rs
@@ -256,7 +256,9 @@ impl TypedModel {
         Ok(())
     }
 
-    pub fn substitute_symbols(&self, subs: &HashMap<Symbol, TDim>) -> TractResult<TypedModel> {
+    /// Bind one or more symbols to concrete values or TDim expressions across
+    /// the whole graph.
+    pub fn set_symbols(&self, subs: &HashMap<Symbol, TDim>) -> TractResult<TypedModel> {
         crate::model::translator::Translate::translate_model(subs, self)
     }
 
@@ -320,7 +322,7 @@ impl Translate<TypedFact, Box<dyn TypedOp>, TypedFact, Box<dyn TypedOp>> for Has
         mapping: &HashMap<OutletId, OutletId>,
     ) -> TractResult<TVec<OutletId>> {
         target.check_consistency()?;
-        let outlets = node.op.substitute_symbols(source, node, target, mapping, self)?;
+        let outlets = node.op.set_symbols(source, node, target, mapping, self)?;
         for &outlet in &outlets {
             let fact = &mut target.nodes[outlet.node].outputs[outlet.slot].fact;
             if fact.shape.volume().is_zero()
diff --git a/core/src/ops/array/broadcast.rs b/core/src/ops/array/broadcast.rs
index 1b86834413..d6fccab489 100644
--- a/core/src/ops/array/broadcast.rs
+++ b/core/src/ops/array/broadcast.rs
@@ -124,7 +124,7 @@ impl TypedOp for MultiBroadcastTo {
         crate::optim::propagate_roi::bubble_roi(model, node)
     }
 
-    fn substitute_symbols(
+    fn set_symbols(
         &self,
         _source: &TypedModel,
         node: &TypedNode,
diff --git a/core/src/ops/array/slice.rs b/core/src/ops/array/slice.rs
index 15a12fb328..e5ccf84a36 100644
--- a/core/src/ops/array/slice.rs
+++ b/core/src/ops/array/slice.rs
@@ -178,7 +178,7 @@ impl TypedOp for Slice {
         }
     }
 
-    fn substitute_symbols(
+    fn set_symbols(
         &self,
         _source: &TypedModel,
         node: &TypedNode,
diff --git a/core/src/ops/array/tile.rs b/core/src/ops/array/tile.rs
index 00e7e10a33..3988779dbf 100644
--- a/core/src/ops/array/tile.rs
+++ b/core/src/ops/array/tile.rs
@@ -45,7 +45,7 @@ impl EvalOp for Tile {
 impl TypedOp for Tile {
     as_op!();
 
-    fn substitute_symbols(
+    fn set_symbols(
         &self,
         _source: &TypedModel,
         node: &TypedNode,
diff --git a/core/src/ops/change_axes.rs b/core/src/ops/change_axes.rs
index 52fad5df56..5b79b4e187 100644
--- a/core/src/ops/change_axes.rs
+++ b/core/src/ops/change_axes.rs
@@ -906,7 +906,7 @@ impl TypedOp for AxisOp {
         Ok(Some(op))
     }
 
-    fn substitute_symbols(
+    fn set_symbols(
         &self,
         _source: &TypedModel,
         node: &TypedNode,
diff --git a/core/src/ops/cnn/deconv/deconv_sum.rs b/core/src/ops/cnn/deconv/deconv_sum.rs
index 04479a9b2e..59b5fe5721 100644
--- a/core/src/ops/cnn/deconv/deconv_sum.rs
+++ b/core/src/ops/cnn/deconv/deconv_sum.rs
@@ -106,7 +106,7 @@ impl TypedOp for DeconvSum {
         Ok(tvec!(inputs[0].datum_type.fact(shape)))
     }
 
-    fn substitute_symbols(
+    fn set_symbols(
         &self,
         _source: &TypedModel,
         node: &TypedNode,
diff --git a/core/src/ops/konst.rs b/core/src/ops/konst.rs
index a2754d50d0..eb23b38b7f 100644
--- a/core/src/ops/konst.rs
+++ b/core/src/ops/konst.rs
@@ -76,7 +76,7 @@ impl TypedOp for Const {
         Ok(tvec!((Cost::Params(self.0.datum_type().unquantized()), self.0.len().into())))
     }
 
-    fn substitute_symbols(
+    fn set_symbols(
         &self,
         _source: &TypedModel,
         node: &TypedNode,
diff --git a/core/src/ops/mod.rs b/core/src/ops/mod.rs
index b69eefc5c8..12db1cc7df 100644
--- a/core/src/ops/mod.rs
+++ b/core/src/ops/mod.rs
@@ -295,7 +295,7 @@ pub trait TypedOp:
     /// expressions (a concrete integer is `TDim::Val(v)`; an expression
     /// can be any other TDim, including symbolic ones).
     #[allow(unused_variables)]
-    fn substitute_symbols(
+    fn set_symbols(
         &self,
         source: &TypedModel,
         node: &TypedNode,
diff --git a/core/src/ops/scan/decluttered.rs b/core/src/ops/scan/decluttered.rs
index 9d638b4cd3..53e3f148f6 100644
--- a/core/src/ops/scan/decluttered.rs
+++ b/core/src/ops/scan/decluttered.rs
@@ -110,18 +110,27 @@ impl Scan {
         // on the first call or when reset_every_turn is set; otherwise the
         // body input is fed from the carried hidden_state.
         //
-        // Inlining is therefore safe iff the caller does not rely on
-        // tract's across-call carry, which we encode as one of:
+        // Inlining is safe iff the caller does not rely on tract's across-call
+        // carry. We accept it when:
         //   - reset_every_turn (carry is cleared every turn anyway), or
-        //   - external_state (caller plumbs the State input every call,
-        //     e.g. parakeet decoder).
-        // Otherwise (internal-managed state, e.g. DFN3 GRU under pulse),
-        // bail. See issue #2157.
-        rule_if!(
-            self.reset_every_turn
-                || self.external_state
-                || !self.input_mapping.iter().any(InputMapping::is_state)
-        );
+        //   - external_state (explicitly asserted, e.g. force_scan_external_state), or
+        //   - there is no State at all, or
+        //   - the caller manages the state: every recurrent state has a
+        //     last-value output that reaches a model output, so the caller can
+        //     read the updated state and feed it back across calls (e.g. DTLN /
+        //     parakeet decoders). A pulse model with tract-managed state (e.g.
+        //     DFN3 GRU) does NOT export its state, so it is not inlined.
+        // See issue #2157.
+        let has_state = self.input_mapping.iter().any(InputMapping::is_state);
+        let state_outputs: Vec<_> = self.output_mapping.iter().filter(|m| m.state).collect();
+        let state_exported = has_state
+            && !state_outputs.is_empty()
+            && state_outputs.iter().all(|m| {
+                m.last_value_slot.is_some_and(|slot| {
+                    Self::outlet_reaches_model_output(model, OutletId::new(node.id, slot))
+                })
+            });
+        rule_if!(self.reset_every_turn || self.external_state || !has_state || state_exported);
         let mut patch = TypedModelPatch::new("Inline single loop scan");
         patch.model = self.body.clone();
         for (outer_wire, inner_wire) in izip!(&node.inputs, &self.body.inputs) {
@@ -138,6 +147,31 @@ impl Scan {
         Ok(Some(patch))
     }
 
+    /// True if `start` (an outlet of this Scan, e.g. a state's last-value
+    /// output) is, or transitively feeds, a model output — i.e. the caller can
+    /// observe the updated state and thread it back across calls. Used to tell a
+    /// caller-managed-state model (safe to inline a single-iteration Scan) from
+    /// a pulse model whose state tract carries internally (must not inline).
+    fn outlet_reaches_model_output(model: &TypedModel, start: OutletId) -> bool {
+        let outputs: std::collections::HashSet<OutletId> = model.outputs.iter().copied().collect();
+        let mut seen: std::collections::HashSet<OutletId> = Default::default();
+        let mut stack = vec![start];
+        while let Some(o) = stack.pop() {
+            if outputs.contains(&o) {
+                return true;
+            }
+            if !seen.insert(o) {
+                continue;
+            }
+            for succ in &model.node(o.node).outputs[o.slot].successors {
+                for slot in 0..model.node(succ.node).outputs.len() {
+                    stack.push(OutletId::new(succ.node, slot));
+                }
+            }
+        }
+        false
+    }
+
     fn declutter_body_axes(
         &self,
         _session: &mut OptimizerSession,
@@ -894,7 +928,7 @@ impl TypedOp for Scan {
         Ok(None)
     }
 
-    fn substitute_symbols(
+    fn set_symbols(
         &self,
         _source: &TypedModel,
         node: &TypedNode,
@@ -907,9 +941,9 @@ impl TypedOp for Scan {
             output_mapping: self
                 .output_mapping
                 .iter()
-                .map(|om| om.substitute_symbols(subs))
+                .map(|om| om.set_symbols(subs))
                 .collect::<TractResult<Vec<_>>>()?,
-            body: self.body.substitute_symbols(subs)?,
+            body: self.body.set_symbols(subs)?,
             ..self.clone()
         };
         target.wire_node(&node.name, op, &inputs)
diff --git a/core/src/ops/scan/mod.rs b/core/src/ops/scan/mod.rs
index 74530f8ec8..f2e8f486a0 100644
--- a/core/src/ops/scan/mod.rs
+++ b/core/src/ops/scan/mod.rs
@@ -52,7 +52,7 @@ impl<F: Clone> OutputMapping<F> {
 }
 
 impl<F: Clone + DimLike> OutputMapping<F> {
-    pub fn substitute_symbols(
+    pub fn set_symbols(
         &self,
         subs: &std::collections::HashMap<Symbol, F>,
     ) -> TractResult<OutputMapping<F>> {
diff --git a/core/src/ops/scan/optimized.rs b/core/src/ops/scan/optimized.rs
index 05245d7a43..db1604f1ab 100644
--- a/core/src/ops/scan/optimized.rs
+++ b/core/src/ops/scan/optimized.rs
@@ -233,6 +233,15 @@ impl OpState for State {
         outputs.sort_by_key(|a| a.0);
         let mut outputs: TVec<Tensor> = outputs.into_iter().map(|(_slot, v)| v).collect();
 
+        // The body runs the SAME plan with the SAME shapes every iteration, so
+        // resolve its symbols once and keep them across iters (light per-iter
+        // reset), and reuse one drained input buffer. This avoids the per-timestep
+        // symbol re-resolution + reallocation a plain `model_state.run()` would do.
+        // Cleared up front since the body state persists across outer Scan calls.
+        model_state.clear_resolved_symbols();
+        let mut iter_inputs: TVec<TValue> = tvec!();
+        let mut symbols_resolved = false;
+
         for i in 0..iters {
             *position += 1;
             if *position <= op.skip {
@@ -240,28 +249,29 @@ impl OpState for State {
             }
             hidden_state.reverse();
 
-            let iter_inputs: TVec<TValue> = op
-                .input_mapping
-                .iter()
-                .enumerate()
-                .map(|(slot, m)| {
-                    Ok(match m {
-                        InputMapping::State => Some(hidden_state.pop().unwrap()),
-                        InputMapping::Scan(info) => Some(
-                            Self::slice_input(&inputs[slot], info.axis, i, info.chunk)?
-                                .into_tvalue(),
-                        ),
-                        InputMapping::Full => Some(inputs[slot].clone()),
-                    })
-                })
-                .collect::<TractResult<Vec<_>>>()?
-                .into_iter()
-                .flatten()
-                .collect();
-
+            iter_inputs.clear();
+            for (slot, m) in op.input_mapping.iter().enumerate() {
+                iter_inputs.push(match m {
+                    InputMapping::State => hidden_state.pop().unwrap(),
+                    InputMapping::Scan(info) => {
+                        Self::slice_input(&inputs[slot], info.axis, i, info.chunk)?.into_tvalue()
+                    }
+                    InputMapping::Full => inputs[slot].clone(),
+                });
+            }
             trace!("iter_inputs #{i}: {iter_inputs:?}");
-            let iter_outputs =
-                model_state.run(iter_inputs).with_context(|| "Evaluating inner body")?;
+
+            // Lighter equivalent of `model_state.run(iter_inputs)`: resolve body
+            // symbols only on the first iteration, and reset between iters without
+            // discarding them.
+            model_state.set_inputs_drain(&mut iter_inputs).context("Setting body inputs")?;
+            if !symbols_resolved {
+                model_state.resolve_symbols_with_states()?;
+                symbols_resolved = true;
+            }
+            model_state.exec().with_context(|| "Evaluating inner body")?;
+            let iter_outputs = model_state.outputs()?;
+            model_state.reset_turn_keep_symbols();
             trace!("iter_outputs #{i}: {iter_outputs:?}");
 
             for (v, mapping) in iter_outputs.into_iter().zip(&op.output_mapping) {
diff --git a/core/src/ops/source.rs b/core/src/ops/source.rs
index 4b4c32244d..20de5a1f6e 100644
--- a/core/src/ops/source.rs
+++ b/core/src/ops/source.rs
@@ -66,7 +66,7 @@ impl TypedOp for TypedSource {
         )))
     }
 
-    fn substitute_symbols(
+    fn set_symbols(
         &self,
         _source: &TypedModel,
         node: &TypedNode,
diff --git a/core/src/plan.rs b/core/src/plan.rs
index 4998dc9e46..216b55d4da 100644
--- a/core/src/plan.rs
+++ b/core/src/plan.rs
@@ -247,11 +247,27 @@ where
     }
     /// Reset wires state.
     pub fn reset_turn(&mut self) -> TractResult<()> {
+        self.reset_turn_keep_symbols();
+        self.turn_state.resolved_symbols = SymbolValues::default();
+        Ok(())
+    }
+
+    /// Like [`reset_turn`] but keeps the resolved symbols (and scenario). Used by
+    /// `Scan`/`Loop` bodies, whose shapes are constant across iterations: it lets
+    /// the body resolve its symbols once and skip the per-iteration re-resolution
+    /// the full `reset_turn` + `run` cycle would otherwise force.
+    pub(crate) fn reset_turn_keep_symbols(&mut self) {
         for node in &self.plan.order {
             self.turn_state.values[*node] = None;
         }
+    }
+
+    /// Clear resolved symbols (and scenario) without touching node values. Used at
+    /// the start of a fresh `Scan` evaluation, since the body state persists across
+    /// outer calls and a previous call may have left stale symbol resolutions.
+    pub(crate) fn clear_resolved_symbols(&mut self) {
         self.turn_state.resolved_symbols = SymbolValues::default();
-        Ok(())
+        self.turn_state.scenario = None;
     }
 
     /// Reset op inner state.
@@ -263,7 +279,7 @@ where
         Ok(())
     }
 
-    fn resolve_symbols_with_states(&mut self) -> TractResult<()> {
+    pub(crate) fn resolve_symbols_with_states(&mut self) -> TractResult<()> {
         for state in self
             .op_states
             .iter_mut()
@@ -470,6 +486,22 @@ where
         Ok(())
     }
 
+    /// Like [`set_inputs`] but drains the caller's buffer (leaving it empty with
+    /// its capacity intact) instead of consuming it, so a repeated caller (a
+    /// `Scan` body loop) can reuse one allocation across iterations.
+    pub(crate) fn set_inputs_drain(&mut self, inputs: &mut TVec<TValue>) -> TractResult<()> {
+        ensure!(
+            inputs.len() == self.model().inputs.len(),
+            "Wrong number of inputs for model. Expected {} got {}",
+            self.model().inputs.len(),
+            inputs.len()
+        );
+        for (ix, t) in inputs.drain(..).enumerate() {
+            self.set_input(ix, t)?
+        }
+        Ok(())
+    }
+
     fn resolve(state: &mut TurnState, expression: &TDim, provided: i64) -> TractResult<()> {
         if let TDim::Sym(sym) = expression
             && state.resolved_symbols.get(sym).is_none()
diff --git a/core/src/runtime.rs b/core/src/runtime.rs
index 06ecbca35a..a63616a72e 100644
--- a/core/src/runtime.rs
+++ b/core/src/runtime.rs
@@ -105,7 +105,7 @@ pub struct DefaultRuntime;
 
 impl Runtime for DefaultRuntime {
     fn name(&self) -> StaticName {
-        Cow::Borrowed("default")
+        Cow::Borrowed("cpu")
     }
 
     fn prepare_with_options(
@@ -215,7 +215,34 @@ pub fn runtimes() -> impl Iterator<Item = &'static dyn Runtime> {
     inventory::iter::<InventorizedRuntime>().filter(|rt| rt.check().is_ok()).map(|ir| ir.0)
 }
 
+/// Known GPU backends, tried in order when resolving the virtual `gpu`
+/// (strict) / `gpu-or-cpu` (best-effort) names.
+const GPU_RUNTIME_NAMES: &[&str] = &["metal", "cuda"];
+
 pub fn runtime_for_name(s: &str) -> TractResult<Option<&'static dyn Runtime>> {
+    // Back-compat: `default` was the original name for the CPU runtime
+    // before it was renamed.  Keep it working as a plain alias.
+    let s = if s == "default" { "cpu" } else { s };
+    if s == "gpu" || s == "gpu-or-cpu" {
+        let mut last_check_err: Option<TractError> = None;
+        for name in GPU_RUNTIME_NAMES {
+            let Some(rt) = inventory::iter::<InventorizedRuntime>().find(|rt| rt.name() == *name)
+            else {
+                continue;
+            };
+            match rt.check() {
+                Ok(()) => return Ok(Some(rt.0)),
+                Err(e) => last_check_err = Some(e),
+            }
+        }
+        if s == "gpu" {
+            let detail =
+                last_check_err.map(|e| format!(" (last backend error: {e:#})")).unwrap_or_default();
+            bail!("Runtime `gpu` requested but no GPU backend is available{detail}");
+        }
+        // gpu-or-cpu: fall through to the cpu runtime.
+        return runtime_for_name("cpu");
+    }
     rule_if_some!(rt = inventory::iter::<InventorizedRuntime>().find(|rt| rt.name() == s));
     rt.check()?;
     Ok(Some(rt.0))
diff --git a/core/src/transform.rs b/core/src/transform.rs
index b83a592f81..03f71632f8 100644
--- a/core/src/transform.rs
+++ b/core/src/transform.rs
@@ -256,16 +256,16 @@ pub enum SymbolValueSpec {
 }
 
 #[derive(Debug, Default, serde::Deserialize)]
-pub struct ConcretizeSymbolsConfig {
+pub struct SetSymbolsConfig {
     pub values: std::collections::HashMap<String, SymbolValueSpec>,
 }
 
 #[derive(Debug)]
-struct ConcretizeSymbolsTransform(ConcretizeSymbolsConfig);
+struct SetSymbolsTransform(SetSymbolsConfig);
 
-impl ModelTransform for ConcretizeSymbolsTransform {
+impl ModelTransform for SetSymbolsTransform {
     fn name(&self) -> StaticName {
-        "concretize_symbols".into()
+        "set_symbols".into()
     }
 
     fn transform(&self, model: &mut TypedModel) -> TractResult<()> {
@@ -281,13 +281,13 @@ impl ModelTransform for ConcretizeSymbolsTransform {
             };
             subs.insert(sym, dim);
         }
-        *model = model.substitute_symbols(&subs)?;
+        *model = model.set_symbols(&subs)?;
         Ok(())
     }
 }
 
-register_model_transform!("concretize_symbols", ConcretizeSymbolsConfig, |config| Ok(Box::new(
-    ConcretizeSymbolsTransform(config)
+register_model_transform!("set_symbols", SetSymbolsConfig, |config| Ok(Box::new(
+    SetSymbolsTransform(config)
 )));
 
 /// Ad-hoc fix-up for NNEF artifacts exported before Scan grew the
@@ -324,7 +324,7 @@ impl ModelTransform for ForceScanExternalState {
             }
         }
         if !subs.is_empty() {
-            *model = model.substitute_symbols(&subs)?;
+            *model = model.set_symbols(&subs)?;
         }
         for node in &mut model.nodes {
             if let Some(scan) = node.op_as_mut::<Scan>() {
@@ -362,6 +362,28 @@ register_model_transform!("select_outputs", SelectOutputsConfig, |config| Ok(Box
     SelectOutputsTransform(config)
 )));
 
+#[derive(Debug, serde::Deserialize, Default)]
+pub struct SelectInputsConfig {
+    pub inputs: Vec<String>,
+}
+
+#[derive(Debug)]
+struct SelectInputsTransform(SelectInputsConfig);
+
+impl ModelTransform for SelectInputsTransform {
+    fn name(&self) -> StaticName {
+        "select_inputs".into()
+    }
+
+    fn transform(&self, model: &mut TypedModel) -> TractResult<()> {
+        model.select_inputs_by_name(self.0.inputs.iter())
+    }
+}
+
+register_model_transform!("select_inputs", SelectInputsConfig, |config| Ok(Box::new(
+    SelectInputsTransform(config)
+)));
+
 inventory::submit! {
     ModelTransformFactory {
         name: "f32_to_f16",
diff --git a/cuda/Cargo.toml b/cuda/Cargo.toml
index 95c4884a8a..0cf4234c78 100644
--- a/cuda/Cargo.toml
+++ b/cuda/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-cuda"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 license = "MIT OR Apache-2.0"
 authors = [
 	"Louis Chouraki <louis.chouraki@sonos.com>",
diff --git a/cuda/src/ops/quant_q81.rs b/cuda/src/ops/quant_q81.rs
index 10c763d2a6..badf21cf56 100644
--- a/cuda/src/ops/quant_q81.rs
+++ b/cuda/src/ops/quant_q81.rs
@@ -104,7 +104,7 @@ impl TypedOp for CudaGgmlQuantQ81 {
         .with_context(|| format!("Error while computing facts for {:?}", self.name()))
     }
 
-    fn substitute_symbols(
+    fn set_symbols(
         &self,
         _source: &TypedModel,
         node: &TypedNode,
diff --git a/data/Cargo.toml b/data/Cargo.toml
index b4db993ed3..76b62b58a1 100644
--- a/data/Cargo.toml
+++ b/data/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-data"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 license = "MIT OR Apache-2.0"
 authors = ["Mathieu Poumeyrol <kali@zoy.org>"]
 description = "Tiny, no-nonsense, self contained, TensorFlow and ONNX inference"
diff --git a/doc/symbolic-shapes.md b/doc/symbolic-shapes.md
index b933a80864..b83187fbdd 100644
--- a/doc/symbolic-shapes.md
+++ b/doc/symbolic-shapes.md
@@ -118,7 +118,7 @@ let b = model.symbols.sym("B");
 let mut subs = HashMap::new();
 subs.insert(s, 224.into());           // S = 224
 subs.insert(b, 1.into());             // B = 1
-let model = model.substitute_symbols(&subs)?;
+let model = model.set_symbols(&subs)?;
 ```
 
 After this, the shapes are pure `Val(_)` and downstream passes treat
@@ -175,11 +175,11 @@ The CLI does the same things via flags:
 
 - `-i N,3,224,224,f32` — set an input fact (per-input).
 - `--set S=224 --set B=1` — bind symbols to constants. Equivalent to
-  `substitute_symbols` on the library side.
+  `set_symbols` on the library side.
 - `--input-from-bundle io.npz` — derive concrete input shapes from
   the tensors actually present in the bundle; runs both "set input
   facts" and "concretise symbols" in one step. The library equivalent
-  is the `set_input_fact` + `substitute_symbols` pair above.
+  is the `set_input_fact` + `set_symbols` pair above.
 
 ## ONNX gotchas
 
diff --git a/examples/nemo-nemotron-asr/src/main.rs b/examples/nemo-nemotron-asr/src/main.rs
index 9de861874c..0585219318 100644
--- a/examples/nemo-nemotron-asr/src/main.rs
+++ b/examples/nemo-nemotron-asr/src/main.rs
@@ -13,13 +13,14 @@ fn argmax(slice: &[f32]) -> Option<usize> {
 }
 
 fn concretize_batch(mut model: Model) -> anyhow::Result<Model> {
-    model.transform(ConcretizeSymbols::new().value("BATCH", 1))?;
+    model.transform(SetSymbols::new().value("BATCH", 1))?;
     Ok(model)
 }
 
 fn remove_length_input(mut model: Model) -> anyhow::Result<Model> {
     model
         .transform(r#"{"name":"patch","body":"length = tract_core_shape_of(input_signal)[1];"}"#)?;
+    model.transform(r#"{"name":"select_inputs","inputs":["input_signal"]}"#)?;
     Ok(model)
 }
 
diff --git a/examples/nemo-nemotron-streaming-asr/src/main.rs b/examples/nemo-nemotron-streaming-asr/src/main.rs
index 8f07c22a5d..4ce7210796 100644
--- a/examples/nemo-nemotron-streaming-asr/src/main.rs
+++ b/examples/nemo-nemotron-streaming-asr/src/main.rs
@@ -104,10 +104,11 @@ impl NemotronModels {
 
         eprint!("Loading preprocessor to {}...", runtime.name()?);
         let mut pp = nnef.load(format!("{assets}/model/preprocessor.nnef.tgz"))?;
-        pp.transform(ConcretizeSymbols::new().value("BATCH", 1))?;
+        pp.transform(SetSymbols::new().value("BATCH", 1))?;
         pp.transform(
             r#"{"name":"patch","body":"length = tract_core_shape_of(input_signal)[1];"}"#,
         )?;
+        pp.transform(r#"{"name":"select_inputs","inputs":["input_signal"]}"#)?;
         pp.transform(r#"{"name":"select_outputs","outputs":["processed_signal"]}"#)?;
         pp.transform(Pulse::new(config.preproc_pulse.to_string()).symbol("INPUT_SIGNAL__TIME"))?;
         let pp_delay = pp.property("pulse.delay")?.as_slice::<i64>()?[0].to_owned() as usize;
@@ -120,11 +121,12 @@ impl NemotronModels {
 
         eprint!("Loading encoder to {}...", runtime.name()?);
         let mut enc = nnef.load(format!("{assets}/model/encoder.p1.nnef.tgz"))?;
-        enc.transform(ConcretizeSymbols::new().value("BATCH", 1))?;
+        enc.transform(SetSymbols::new().value("BATCH", 1))?;
         enc.transform("transformers_detect_all")?;
         enc.transform(
             r#"{"name":"patch","body":"length = tract_core_shape_of(audio_signal)[2];"}"#,
         )?;
+        enc.transform(r#"{"name":"select_inputs","inputs":["audio_signal"]}"#)?;
         enc.transform(r#"{"name":"select_outputs","outputs":["outputs"]}"#)?;
         enc.transform(Pulse::new(config.encoder_pulse.to_string()).symbol("AUDIO_SIGNAL__TIME"))?;
         let enc_delay = enc.property("pulse.delay")?.as_slice::<i64>()?[0].to_owned() as usize;
@@ -137,14 +139,14 @@ impl NemotronModels {
 
         eprint!("Loading decoder to {}...", runtime.name()?);
         let mut dec = nnef.load(format!("{assets}/model/decoder.nnef.tgz"))?;
-        dec.transform(ConcretizeSymbols::new().value("BATCH", 1).value("TARGETS__TIME", 1))?;
+        dec.transform(SetSymbols::new().value("BATCH", 1).value("TARGETS__TIME", 1))?;
         let decoder = runtime.prepare(dec)?;
         eprintln!(" done.");
 
         eprint!("Loading joint to {}...", runtime.name()?);
         let mut jnt = nnef.load(format!("{assets}/model/joint.nnef.tgz"))?;
         jnt.transform(
-            ConcretizeSymbols::new()
+            SetSymbols::new()
                 .value("BATCH", 1)
                 .value("ENCODER_OUTPUTS__TIME", 1)
                 .value("DECODER_OUTPUTS__TIME", 1),
diff --git a/examples/wasm-model-bench/src/bench_onnx.rs b/examples/wasm-model-bench/src/bench_onnx.rs
index 906d35154b..98830d90c5 100644
--- a/examples/wasm-model-bench/src/bench_onnx.rs
+++ b/examples/wasm-model-bench/src/bench_onnx.rs
@@ -49,7 +49,7 @@ fn main() -> Result<()> {
     let symbols_env = std::env::var("TRACT_BENCH_SYMBOLS").ok().filter(|s| !s.is_empty());
 
     // When symbols are provided, the model is symbolic-shaped and we go straight
-    // to TypedModel → substitute_symbols, ignoring shape_spec (input shapes will
+    // to TypedModel → set_symbols, ignoring shape_spec (input shapes will
     // be derived from the symbol substitution). When no symbols, we use the
     // shape_spec to pin input facts on the InferenceModel before into_typed.
     let typed = if let Some(symbols_str) = symbols_env {
@@ -60,7 +60,7 @@ fn main() -> Result<()> {
             let sym = typed.symbols.sym(k);
             subs.insert(sym, TDim::Val(v.parse::<i64>()?));
         }
-        typed.substitute_symbols(&subs)?
+        typed.set_symbols(&subs)?
     } else {
         if let Some(spec) = shape_spec.as_deref().filter(|s| *s != "-") {
             for (i, one) in spec.split(';').enumerate() {
diff --git a/extra/Cargo.toml b/extra/Cargo.toml
index 29a20712c7..d3c2a3649c 100644
--- a/extra/Cargo.toml
+++ b/extra/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-extra"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 license = "MIT OR Apache-2.0"
 authors = ["Mathieu Poumeyrol <kali@zoy.org>"]
 description = "Tiny, no-nonsense, self contained, TensorFlow and ONNX inference"
diff --git a/gpu/Cargo.toml b/gpu/Cargo.toml
index 4c5bd73aa6..2d53fc0768 100644
--- a/gpu/Cargo.toml
+++ b/gpu/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-gpu"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 license = "MIT OR Apache-2.0"
 authors = [
 	"Hubert de La Jonquiere <hubert.delajonquiere@sonos.com>",
diff --git a/gpu/src/ops/change_axes.rs b/gpu/src/ops/change_axes.rs
index 847cbe7dfe..f456ecfff0 100644
--- a/gpu/src/ops/change_axes.rs
+++ b/gpu/src/ops/change_axes.rs
@@ -162,7 +162,7 @@ impl TypedOp for GpuAxisOp {
         self.inner.axes_mapping(&ref_inputs, &ref_outputs)
     }
 
-    fn substitute_symbols(
+    fn set_symbols(
         &self,
         _source: &TypedModel,
         node: &TypedNode,
diff --git a/gpu/src/ops/slice.rs b/gpu/src/ops/slice.rs
index 925bc4bf42..aac38496bc 100644
--- a/gpu/src/ops/slice.rs
+++ b/gpu/src/ops/slice.rs
@@ -94,7 +94,7 @@ impl TypedOp for GpuSlice {
             .with_context(|| format!("Error while computing facts for {:?}", self.name()))
     }
 
-    fn substitute_symbols(
+    fn set_symbols(
         &self,
         _source: &TypedModel,
         node: &TypedNode,
diff --git a/harness/core-proptest-pulse/src/lib.rs b/harness/core-proptest-pulse/src/lib.rs
index faaccb07ae..a8866e9294 100644
--- a/harness/core-proptest-pulse/src/lib.rs
+++ b/harness/core-proptest-pulse/src/lib.rs
@@ -47,7 +47,7 @@ fn proptest_regular_against_pulse(
     let subs =
         std::collections::HashMap::from([(s.clone(), tract_data::prelude::TDim::Val(len as i64))]);
 
-    let concrete = model.clone().substitute_symbols(&subs).unwrap();
+    let concrete = model.clone().set_symbols(&subs).unwrap();
     if concrete.nodes.iter().any(|n| n.outputs.iter().any(|o| o.fact.shape.volume().is_zero())) {
         return Err(TestCaseError::reject("too short input"));
     }
diff --git a/harness/nemotron-speech-streaming-en-0.6b/ci.sh b/harness/nemotron-speech-streaming-en-0.6b/ci.sh
index 5b3697e60b..75055a4f7d 100755
--- a/harness/nemotron-speech-streaming-en-0.6b/ci.sh
+++ b/harness/nemotron-speech-streaming-en-0.6b/ci.sh
@@ -46,16 +46,18 @@ model_prefix=$MODELS/$S3DIR/$MODEL
 # Check that the patch transform eliminates all Iff nodes,
 # and that select_outputs can reduce the model to a single output
 $TRACT_RUN $model_prefix.preprocessor.nnef.tgz \
-	-t 'concretize_symbols(values: {"BATCH": 1})' \
+	-t 'set_symbols(values: {"BATCH": 1})' \
 	-t 'patch(body: "length = tract_core_shape_of(input_signal)[1];")' \
+	-t 'select_inputs(inputs: ["input_signal"])' \
 	-t 'select_outputs(outputs: ["processed_signal"])' \
 	dump -q \
 	--assert-op-count Iff 0
 
 # Check that the preprocessor can be pulsified
 $TRACT_RUN $model_prefix.preprocessor.nnef.tgz \
-	-t 'concretize_symbols(values: {"BATCH": 1})' \
+	-t 'set_symbols(values: {"BATCH": 1})' \
 	-t 'patch(body: "length = tract_core_shape_of(input_signal)[1];")' \
+	-t 'select_inputs(inputs: ["input_signal"])' \
 	-t 'select_outputs(outputs: ["processed_signal"])' \
 	-t 'pulse(symbol: Some("INPUT_SIGNAL__TIME"), pulse: "4800")' \
 	dump -q
@@ -79,14 +81,14 @@ do
 		*) continue;;
 	esac
 	$TRACT_RUN $model_prefix.preprocessor.nnef.tgz $rt \
-		-t 'concretize_symbols(values: {"BATCH": 1})' \
+		-t 'set_symbols(values: {"BATCH": 1})' \
 		-t 'patch(body: "length = tract_core_shape_of(input_signal)[1];")' \
 		-t 'select_outputs(outputs: ["processed_signal"])' \
 		-t 'pulse(symbol: Some("INPUT_SIGNAL__TIME"), pulse: "4800")' \
 		dump -q $pp_assert
 	$TRACT_RUN $model_prefix.encoder.p1.nnef.tgz $rt \
 		--nnef-tract-transformers \
-		-t 'concretize_symbols(values: {"BATCH": 1})' \
+		-t 'set_symbols(values: {"BATCH": 1})' \
 		-t 'patch(body: "length = tract_core_shape_of(audio_signal)[2];")' \
 		-t 'select_outputs(outputs: ["outputs"])' \
 		-t 'pulse(symbol: Some("AUDIO_SIGNAL__TIME"), pulse: "112")' \
@@ -99,8 +101,9 @@ done
 # must be 14 * 8 = 112 audio frames.
 $TRACT_RUN $model_prefix.encoder.p1.nnef.tgz \
 	--nnef-tract-transformers \
-	-t 'concretize_symbols(values: {"BATCH": 1})' \
+	-t 'set_symbols(values: {"BATCH": 1})' \
 	-t 'patch(body: "length = tract_core_shape_of(audio_signal)[2];")' \
+	-t 'select_inputs(inputs: ["audio_signal"])' \
 	-t 'select_outputs(outputs: ["outputs"])' \
 	-t 'pulse(symbol: Some("AUDIO_SIGNAL__TIME"), pulse: "112")' \
 	dump -q
@@ -110,8 +113,9 @@ $TRACT_RUN $model_prefix.encoder.p1.nnef.tgz \
 # and the output comparison is trimmed accordingly.
 $TRACT_RUN $model_prefix.encoder.p1.nnef.tgz \
 	--nnef-tract-transformers \
-	-t 'concretize_symbols(values: {"BATCH": 1})' \
+	-t 'set_symbols(values: {"BATCH": 1})' \
 	-t 'patch(body: "length = tract_core_shape_of(audio_signal)[2];")' \
+	-t 'select_inputs(inputs: ["audio_signal"])' \
 	-t 'select_outputs(outputs: ["outputs"])' \
 	-t 'pulse(symbol: Some("AUDIO_SIGNAL__TIME"), pulse: "112")' \
 	run \
diff --git a/harness/nnef-test-cases/conv-then-shape-of-mask/runme.sh b/harness/nnef-test-cases/conv-then-shape-of-mask/runme.sh
index 2faa03e324..07af5af9b7 100755
--- a/harness/nnef-test-cases/conv-then-shape-of-mask/runme.sh
+++ b/harness/nnef-test-cases/conv-then-shape-of-mask/runme.sh
@@ -7,7 +7,7 @@ set -ex
 
 # Batch mode: S=8 -> conv output T = 1 + 8/2 = 5 frames; the add is fine.
 $TRACT_RUN --nnef-tract-core . \
-    -t 'concretize_symbols(values: {"S": 8})' \
+    -t 'set_symbols(values: {"S": 8})' \
     run --allow-random-input -q
 
 # Streaming compare: pulse=4 -> conv produces 2 frames/step.  The
diff --git a/harness/nnef-test-cases/slice-of-static-with-streaming-size/runme.sh b/harness/nnef-test-cases/slice-of-static-with-streaming-size/runme.sh
index 526d204fcb..cca6b81524 100755
--- a/harness/nnef-test-cases/slice-of-static-with-streaming-size/runme.sh
+++ b/harness/nnef-test-cases/slice-of-static-with-streaming-size/runme.sh
@@ -7,7 +7,7 @@ set -ex
 
 # Batch mode: concretize S=8 -> pe_table[0:8, :] + input[0:8, :]
 $TRACT_RUN --nnef-tract-core . \
-    -t 'concretize_symbols(values: {"S": 8})' \
+    -t 'set_symbols(values: {"S": 8})' \
     run --allow-random-input -q
 
 # Streaming compare: pulse=4.  Each step slices pe_table[0:4, :] (constant
diff --git a/harness/tf-inceptionv3/Cargo.toml b/harness/tf-inceptionv3/Cargo.toml
index 4d5a56dd56..be5be5472e 100644
--- a/harness/tf-inceptionv3/Cargo.toml
+++ b/harness/tf-inceptionv3/Cargo.toml
@@ -9,9 +9,6 @@ edition = "2024"
 image.workspace = true
 tract-tensorflow.workspace = true
 
-[features]
-conform = [ "tract-tensorflow/conform" ]
-
 [dev-dependencies]
 criterion.workspace = true
 dinghy-test.workspace = true
diff --git a/harness/tf-inceptionv3/benches/inceptionv3.rs b/harness/tf-inceptionv3/benches/inceptionv3.rs
index 649bef25fd..8fc988fd70 100644
--- a/harness/tf-inceptionv3/benches/inceptionv3.rs
+++ b/harness/tf-inceptionv3/benches/inceptionv3.rs
@@ -16,25 +16,6 @@ pub fn hopper() -> path::PathBuf {
     test_project_path().join(HOPPER)
 }
 
-#[cfg(feature = "conform")]
-fn dummy(_bencher: &mut Criterion) {
-    tract_tensorflow::conform::tf::for_path(tf_inceptionv3::inception_v3_2016_08_28_frozen())
-        .unwrap();
-}
-
-#[cfg(feature = "conform")]
-fn tf(bencher: &mut Criterion) {
-    let mut tf =
-        tract_tensorflow::conform::tf::for_path(tf_inceptionv3::inception_v3_2016_08_28_frozen())
-            .unwrap();
-    let input = tf_inceptionv3::load_image(hopper());
-    bencher.bench_function("tensorflow", move |b| {
-        b.iter(|| {
-            tf.run(vec![("input", input.clone())], "InceptionV3/Predictions/Reshape_1").unwrap()
-        })
-    });
-}
-
 fn tract(bencher: &mut Criterion) {
     let mut tfd =
         tensorflow().model_for_path(tf_inceptionv3::inception_v3_2016_08_28_frozen()).unwrap();
@@ -46,11 +27,6 @@ fn tract(bencher: &mut Criterion) {
 
 pub fn benches() {
     let mut criterion: Criterion = Criterion::default().sample_size(3).configure_from_args();
-    #[cfg(feature = "conform")]
-    {
-        dummy(&mut criterion);
-        tf(&mut criterion);
-    }
     tract(&mut criterion);
 }
 criterion_main!(benches);
diff --git a/hir/Cargo.toml b/hir/Cargo.toml
index 4dde2037a3..0274739ab0 100644
--- a/hir/Cargo.toml
+++ b/hir/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-hir"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 license = "MIT OR Apache-2.0"
 authors = ["Mathieu Poumeyrol <kali@zoy.org>"]
 description = "Tiny, no-nonsense, self contained, TensorFlow and ONNX inference"
diff --git a/libcli/Cargo.toml b/libcli/Cargo.toml
index 157002f031..a3ea505f63 100644
--- a/libcli/Cargo.toml
+++ b/libcli/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-libcli"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 license = "MIT OR Apache-2.0"
 authors = ["Mathieu Poumeyrol <kali@zoy.org>"]
 description = "Tiny, no-nonsense, self contained, TensorFlow and ONNX inference"
@@ -35,8 +35,8 @@ tract-transformers = { workspace = true, optional = true }
 tract-metal = { workspace = true }
 
 [target.'cfg(any(target_os = "linux", target_os = "windows"))'.dependencies]
-cudarc.workspace = true
-tract-cuda.workspace = true
+cudarc = { workspace = true, optional = true }
+tract-cuda = { workspace = true, optional = true }
 
 [features]
 default = ["transformers"]
@@ -45,3 +45,8 @@ hir = []
 onnx = ["tract-onnx"]
 complex = ["tract-core/complex"]
 transformers = ["tract-transformers"]
+# Marker / dependency selector for cudarc-backed code paths
+# (`--cuda-gpu-trace`).  Enabled transitively by tract-cli's cuda-XXXXX
+# features.  Always pulled together — picking one selects the cudarc API
+# binding; this feature wires the optional dep in.
+cuda = ["dep:cudarc", "dep:tract-cuda"]
diff --git a/libcli/src/lib.rs b/libcli/src/lib.rs
index 5527554d58..3246b5d4a3 100644
--- a/libcli/src/lib.rs
+++ b/libcli/src/lib.rs
@@ -14,7 +14,7 @@ pub mod time;
 
 use tract_core::internal::*;
 #[allow(unused_imports)]
-#[cfg(any(target_os = "linux", target_os = "windows"))]
+#[cfg(all(any(target_os = "linux", target_os = "windows"), feature = "cuda"))]
 use tract_cuda::utils::ensure_cuda_runtime_dependencies;
 
 pub fn capture_gpu_trace<F>(matches: &clap::ArgMatches, func: F) -> TractResult<()>
@@ -45,7 +45,7 @@ where
             bail!("`--metal-gpu-trace` present but it is only available on MacOS and iOS")
         }
     } else if matches.get_flag("cuda-gpu-trace") {
-        #[cfg(any(target_os = "linux", target_os = "windows"))]
+        #[cfg(all(any(target_os = "linux", target_os = "windows"), feature = "cuda"))]
         {
             ensure_cuda_runtime_dependencies(
                 "`--cuda-gpu-trace` present but no CUDA installation has been found",
@@ -53,9 +53,12 @@ where
             let _prof = cudarc::driver::safe::Profiler::new()?;
             func()
         }
-        #[cfg(not(any(target_os = "linux", target_os = "windows")))]
+        #[cfg(not(all(any(target_os = "linux", target_os = "windows"), feature = "cuda")))]
         {
-            bail!("`--cuda-gpu-trace` present but it is only available on Linux and Windows")
+            bail!(
+                "`--cuda-gpu-trace` present but tract was not built with CUDA support \
+                 (re-build on Linux/Windows with one of the cuda-XXXXX features)"
+            )
         }
     } else {
         func()
diff --git a/linalg/Cargo.toml b/linalg/Cargo.toml
index 68955ac179..81d3111e31 100644
--- a/linalg/Cargo.toml
+++ b/linalg/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-linalg"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 license = "MIT OR Apache-2.0"
 authors = ["Mathieu Poumeyrol <kali@zoy.org>"]
 description = "Tiny, no-nonsense, self contained, TensorFlow and ONNX inference"
@@ -83,6 +83,10 @@ harness = false
 name = "mm_for_asr_am"
 harness = false
 
+[[bench]]
+name = "qmmm_i8"
+harness = false
+
 [[bench]]
 name = "hardswish"
 harness = false
@@ -136,6 +140,14 @@ harness = false
 name = "avx512_zombies"
 harness = false
 
+[[bench]]
+name = "activations_avx512"
+harness = false
+
 [[bench]]
 name = "wasm"
 harness = false
+
+[[bench]]
+name = "vnni_i32"
+harness = false
diff --git a/linalg/arm64/arm64simd/arm64simd_mmm_i32_8x8_dot.S.j2 b/linalg/arm64/arm64simd/arm64simd_mmm_i32_8x8_dot.S.j2
new file mode 100644
index 0000000000..0a63a74edf
--- /dev/null
+++ b/linalg/arm64/arm64simd/arm64simd_mmm_i32_8x8_dot.S.j2
@@ -0,0 +1,235 @@
+// vim: ft=arm
+
+// C tile regs:
+// - x19-x29 to preserve (but x19, x28, x29 not used) 
+// - d8..d15 to preserve
+// - v16 to v31, no need to preserve
+// 
+//      v16[0] v18[0] v20[0] v22[0] v24[0] v26[0] v28[0] v30[0]
+//      v16[1] v18[1] 
+//      v16[2] v18[2] 
+//      v16[3] v18[3]
+//                     
+//      v17[0] v19[0] v21[0] v23[0] v25[0] v27[0] v29[0] v31[0]
+//      v17[1] v19[1] 
+//      v17[2] v19[2] 
+//      v17[3] v19[3] 
+
+// no preservation either for v0-v7...
+// packed A buffering (2x8 values): alternating v0, v1 with v2, v3
+// packed B buffering (2x8 values): alternating v4, v5 with v6, v7
+
+.text
+.align 4
+
+.cpu generic+fp+simd+dotprod
+.global {{G}}arm64simd_mmm_i32_8x8_dot_{{suffix}}
+{{G}}arm64simd_mmm_i32_8x8_dot_{{suffix}}:
+
+/*
+    prfm        pldl1keep, [x1]
+    prfm        pldl1keep, [x2]
+*/
+    stp         x20, x21, [sp, #-16]!
+    stp         x22, x23, [sp, #-16]!
+    stp         x24, x25, [sp, #-16]!
+    stp         x26, x27, [sp, #-16]!
+
+    stp         d8, d9, [sp, #-16]!
+    stp         d10, d11, [sp, #-16]!
+    stp         d12, d13, [sp, #-16]!
+    stp         d14, d15, [sp, #-16]!
+
+{% include "dispatcher.j2" %}
+
+.add_mat_mul:
+    ldp         x2, x4, [x0, #24]   // b, packing
+    ldp         x3, x1, [x0, #8]    // k, a
+
+    cmp         x3, #0
+    beq         .non_linear_loop
+
+    cmp         x4, #1
+    beq         .packed_packed_loop_1_i8i8
+
+.packed_packed_loop_1:
+
+    ld1	        { v0.4s, v1.4s }, [ x1 ], #32
+    ld1	        { v4.4s, v5.4s }, [ x2 ], #32
+
+    mla         v16.4s, v0.4s, v4.s[0]
+    mla         v17.4s, v1.4s, v4.s[0]
+    mla         v18.4s, v0.4s, v4.s[1]
+    mla         v19.4s, v1.4s, v4.s[1]
+
+    mla         v20.4s, v0.4s, v4.s[2]
+    mla         v21.4s, v1.4s, v4.s[2]
+    mla         v22.4s, v0.4s, v4.s[3]
+    mla         v23.4s, v1.4s, v4.s[3]
+
+    mla         v24.4s, v0.4s, v5.s[0]
+    mla         v25.4s, v1.4s, v5.s[0]
+    mla         v26.4s, v0.4s, v5.s[1]
+    mla         v27.4s, v1.4s, v5.s[1]
+
+    mla         v28.4s, v0.4s, v5.s[2]
+    mla         v29.4s, v1.4s, v5.s[2]
+    mla         v30.4s, v0.4s, v5.s[3]
+    mla         v31.4s, v1.4s, v5.s[3]
+
+    subs        x3, x3, #1
+    bne .packed_packed_loop_1
+
+    b .non_linear_loop
+
+.packed_packed_loop_1_i8i8:
+    // PackedI8K4 (K=4-inner, r=8): per 4-K block, A is m0-3 (v0) / m4-7 (v1),
+    // B is n0-3 (v4) / n4-7 (v5), each lane a 4xi8 group. SDOT by-element dots
+    // a B column's 4 K against all 4 m rows of an A half. Same v16..v31 tile
+    // layout as the SMLAL kernel: v[16 + n*2 + m_half] = C[m_half*4..][n].
+    ld1         { v0.16b, v1.16b }, [ x1 ], #32
+    ld1         { v4.16b, v5.16b }, [ x2 ], #32
+
+    sdot        v16.4s, v0.16b, v4.4b[0]
+    sdot        v17.4s, v1.16b, v4.4b[0]
+    sdot        v18.4s, v0.16b, v4.4b[1]
+    sdot        v19.4s, v1.16b, v4.4b[1]
+    sdot        v20.4s, v0.16b, v4.4b[2]
+    sdot        v21.4s, v1.16b, v4.4b[2]
+    sdot        v22.4s, v0.16b, v4.4b[3]
+    sdot        v23.4s, v1.16b, v4.4b[3]
+
+    sdot        v24.4s, v0.16b, v5.4b[0]
+    sdot        v25.4s, v1.16b, v5.4b[0]
+    sdot        v26.4s, v0.16b, v5.4b[1]
+    sdot        v27.4s, v1.16b, v5.4b[1]
+    sdot        v28.4s, v0.16b, v5.4b[2]
+    sdot        v29.4s, v1.16b, v5.4b[2]
+    sdot        v30.4s, v0.16b, v5.4b[3]
+    sdot        v31.4s, v1.16b, v5.4b[3]
+
+    subs        x3, x3, #4
+    bgt .packed_packed_loop_1_i8i8
+
+    b .non_linear_loop
+
+{% set from = 16 %}{% set to = 31 %}{% include "arm64simd_mmm_i32_scalars.j2" %}
+{% set mr = 8 %}{% set from = 16 %}{% set to = 31 %}{% include "arm64simd_mmm_i32_per_rows.j2" %}
+{% set mr = 8 %}{% set from = 16 %}{% set to = 31 %}{% include "arm64simd_mmm_i32_per_cols.j2" %}
+{% set from = 16 %}{% set to = 31 %}{% include "arm64simd_mmm_load_tile.j2" %}
+
+.add_unicast:
+    ldp         x5, x6, [x0, #8]
+    ldp         x7, x8, [x0, #24]
+
+    cmp         x8, #4
+    beq         non_linear_addc_i32
+
+    {% for col in range(8, 16) %}
+        mov x4, x5
+        {% for reg in range(0, 2) %}
+            {% for lane in range(0, 4) %}
+                ld1 {v0.b}[{{lane}}], [ x4 ], x6
+            {% endfor %}
+            sshll v0.8h, v0.8b, 0
+            sshll v0.4s, v0.4h, 0
+            add v{{ col * 2 + reg }}.4s, v{{ col * 2 + reg }}.4s, v0.4s
+        {% endfor %}
+        add x5, x5, x7
+    {% endfor %}
+
+    b           .non_linear_loop
+
+non_linear_addc_i32:
+    {% for col in range(8, 16) %}
+        mov x4, x5
+        {% for reg in range(0, 2) %}
+            {% for lane in range(0, 4) %}
+                ld1 {v0.s}[{{lane}}], [ x4 ], x6
+            {% endfor %}
+            add v{{ col * 2 + reg }}.4s, v{{ col * 2 + reg }}.4s, v0.4s
+        {% endfor %}
+        add x5, x5, x7
+    {% endfor %}
+
+    b           .non_linear_loop
+
+.add_row_col_products:
+    ldr     x2, [x0, #8]
+    ldr     x3, [x0, #16]
+
+    ld1         { v0.4s, v1.4s }, [ x2 ]
+    ld1         { v4.4s, v5.4s }, [ x3 ]
+
+    xtn         v0.4h, v0.4s
+    xtn         v1.4h, v1.4s
+    xtn         v4.4h, v4.4s
+    xtn         v5.4h, v5.4s
+
+    smlal        v16.4s, v0.4h, v4.h[0]
+    smlal        v17.4s, v1.4h, v4.h[0]
+    smlal        v18.4s, v0.4h, v4.h[1]
+    smlal        v19.4s, v1.4h, v4.h[1]
+    smlal        v20.4s, v0.4h, v4.h[2]
+    smlal        v21.4s, v1.4h, v4.h[2]
+    smlal        v22.4s, v0.4h, v4.h[3]
+    smlal        v23.4s, v1.4h, v4.h[3]
+
+    smlal        v24.4s, v0.4h, v5.h[0]
+    smlal        v25.4s, v1.4h, v5.h[0]
+    smlal        v26.4s, v0.4h, v5.h[1]
+    smlal        v27.4s, v1.4h, v5.h[1]
+    smlal        v28.4s, v0.4h, v5.h[2]
+    smlal        v29.4s, v1.4h, v5.h[2]
+    smlal        v30.4s, v0.4h, v5.h[3]
+    smlal        v31.4s, v1.4h, v5.h[3]
+
+    b           .non_linear_loop
+
+    {% include "arm64simd_mmm_i32_scale_q16_q31.j2" %}
+
+.store:
+    ldp         x5, x6, [x0, #8]            // c base ptr, rsc
+    ldp         x7, x8, [x0, #24]           // csc, item_size
+
+    cmp         x8, #4
+    beq         .store_strides_i32
+
+    {% for col in range(8, 16) %}
+        mov x4, x5
+        {% for reg in range(0, 2) %}
+            {% for lane in range(0, 4) %}
+                st1 { v{{ col * 2 + reg }}.b }[{{ lane * 4 }}], [ x4 ], x6
+            {% endfor %}
+        {% endfor %}
+        add x5, x5, x7
+    {% endfor %}
+
+    b           .non_linear_loop
+
+.store_strides_i32:
+    {% for col in range(8, 16) %}
+        mov x4, x5
+        {% for reg in range(0, 2) %}
+            {% for lane in range(0, 4) %}
+                st1 { v{{ col * 2 + reg }}.s }[{{lane}}], [ x4 ], x6
+            {% endfor %}
+        {% endfor %}
+        add x5, x5, x7
+    {% endfor %}
+
+    b           .non_linear_loop
+
+.return:
+    ldp         d14, d15, [sp], #16
+    ldp         d12, d13, [sp], #16
+    ldp         d10, d11, [sp], #16
+    ldp         d8, d9, [sp], #16
+
+    ldp         x26, x27, [sp], #16
+    ldp         x24, x25, [sp], #16
+    ldp         x22, x23, [sp], #16
+    ldp         x20, x21, [sp], #16
+
+    ret
+
diff --git a/linalg/arm64/arm64simd/dummy_dotprod.S b/linalg/arm64/arm64simd/dummy_dotprod.S
new file mode 100644
index 0000000000..4304549674
--- /dev/null
+++ b/linalg/arm64/arm64simd/dummy_dotprod.S
@@ -0,0 +1,13 @@
+// Build-time capability probe for the assembler, used by build.rs
+// (assembler_supports_dotprod). Older binutils — notably the Debian stretch
+// aarch64 cross-toolchain in CI — predate FEAT_DotProd and cannot assemble
+// `sdot` even with `.cpu generic+fp+simd+dotprod`. If this file fails to
+// assemble, build.rs skips the SDOT kernel and the `tract_arm64_dotprod` cfg,
+// and the runtime falls back to the SMLAL 8x8 i32 kernel. Not linked into
+// anything.
+.cpu generic+fp+simd+dotprod
+.text
+.globl tract_dotprod_probe
+tract_dotprod_probe:
+    sdot v0.4s, v1.16b, v2.4b[0]
+    ret
diff --git a/linalg/benches/activations_avx512.rs b/linalg/benches/activations_avx512.rs
new file mode 100644
index 0000000000..f29ca73152
--- /dev/null
+++ b/linalg/benches/activations_avx512.rs
@@ -0,0 +1,108 @@
+// Microbenchmark: AVX-512 (zmm, 16-wide) element-wise activation kernels vs
+// their x86 predecessor.
+//
+//   sigmoid, tanh              : predecessor = FMA (256-bit, 8-wide) kernel
+//   hardswish, leaky_relu,
+//   silu, gelu                 : predecessor = generic scalar kernel
+//                                (no FMA kernel exists on x86)
+//
+// All buffers are 64-byte aligned (AVX-512 alignment_bytes) and a multiple of
+// 64 elements so every kernel's nr() divides the length. Criterion reports the
+// distribution; the min of the samples is the relevant "min-of-N" number.
+
+use criterion::*;
+use tract_data::prelude::*;
+use tract_linalg::element_wise::ElementWiseKer;
+
+const N: usize = 1024;
+
+fn aligned_input() -> Tensor {
+    let mut t = unsafe { Tensor::uninitialized_aligned::<f32>(&[N], 64).unwrap() };
+    let s = unsafe { t.as_slice_mut_unchecked::<f32>() };
+    for (i, x) in s.iter_mut().enumerate() {
+        *x = (i as f32 / 10.0).sin() * 5.0;
+    }
+    t
+}
+
+// Enable FTZ/DAZ (flush-to-zero, denormals-are-zero) for the whole process so
+// repeated in-place application of a kernel to its own output cannot collapse
+// into denormal arithmetic (extremely slow on x86) and distort the timing.
+// Mirrors what the sigmoid/tanh kernels already do internally via MXCSR.
+#[cfg(target_arch = "x86_64")]
+fn enable_ftz_daz() {
+    // Set MXCSR bit 15 (FTZ) and bit 6 (DAZ) directly; the safe intrinsic
+    // wrappers are deprecated in favour of inline asm.
+    unsafe {
+        let mut mxcsr: u32 = 0;
+        std::arch::asm!("stmxcsr [{p}]", p = in(reg) &mut mxcsr);
+        mxcsr |= (1 << 15) | (1 << 6);
+        std::arch::asm!("ldmxcsr [{p}]", p = in(reg) &mxcsr);
+    }
+}
+
+// In-place throughput, matching the convention of the existing element-wise
+// benches (sigmoid.rs / silu.rs).
+macro_rules! bench_pair {
+    ($c:expr, $name:expr, $pred_label:expr, $pred:ty, $avx512:ty $(, $param:expr)?) => {{
+        let mut group = $c.benchmark_group($name);
+        group.throughput(Throughput::Elements(N as u64));
+        let mut tp = aligned_input();
+        let sp = unsafe { tp.as_slice_mut_unchecked::<f32>() };
+        group.bench_function($pred_label, |b| {
+            b.iter(|| <$pred>::run(sp, ($($param)?)))
+        });
+        if std::is_x86_feature_detected!("avx512f") {
+            let mut ta = aligned_input();
+            let sa = unsafe { ta.as_slice_mut_unchecked::<f32>() };
+            group.bench_function("avx512", |b| {
+                b.iter(|| <$avx512>::run(sa, ($($param)?)))
+            });
+        }
+        group.finish();
+    }};
+}
+
+fn benches(c: &mut Criterion) {
+    #[cfg(target_arch = "x86_64")]
+    enable_ftz_daz();
+    use tract_linalg::x86_64_fma::act::*;
+    use tract_linalg::x86_64_fma::{
+        avx512_sigmoid_f32, avx512_tanh_f32, fma_sigmoid_f32, fma_tanh_f32,
+    };
+
+    bench_pair!(c, "sigmoid_f32", "fma", fma_sigmoid_f32, avx512_sigmoid_f32);
+    bench_pair!(c, "tanh_f32", "fma", fma_tanh_f32, avx512_tanh_f32);
+    bench_pair!(
+        c,
+        "hardswish_f32",
+        "generic",
+        tract_linalg::generic::SHardSwish4,
+        x86_64_avx512_hardswish_f32_64n
+    );
+    bench_pair!(
+        c,
+        "leaky_relu_f32",
+        "generic",
+        tract_linalg::generic::SLeakyRelu4,
+        x86_64_avx512_leaky_relu_f32_64n,
+        0.1f32
+    );
+    bench_pair!(
+        c,
+        "silu_f32",
+        "generic",
+        tract_linalg::generic::SSiLU4,
+        x86_64_avx512_silu_f32_16n
+    );
+    bench_pair!(
+        c,
+        "gelu_f32",
+        "generic",
+        tract_linalg::generic::SGelu4,
+        x86_64_avx512_gelu_f32_16n
+    );
+}
+
+criterion_group!(g, benches);
+criterion_main!(g);
diff --git a/linalg/benches/qmmm_i8.rs b/linalg/benches/qmmm_i8.rs
new file mode 100644
index 0000000000..38c234b771
--- /dev/null
+++ b/linalg/benches/qmmm_i8.rs
@@ -0,0 +1,56 @@
+// int8 -> i32 GEMM (qmmm_i32) microbench. A/B the SME SMOPA kernel vs the NEON
+// fallback by running twice: default (SME) vs TRACT_SME_DISABLE=1 (arm64simd 8x8).
+extern crate criterion;
+use criterion::*;
+use tract_data::internal::*;
+use tract_linalg::mmm::{AsInputValue, FusedSpec};
+
+use DatumType::I32;
+
+fn qmmm(be: &mut criterion::Bencher, &(m, k, n): &(usize, usize, usize)) {
+    unsafe {
+        let mmm = tract_linalg::ops().mmm(I32, Some(m), Some(k), Some(n)).unwrap();
+        // packing index 1 == i8i8 for both sme_qmmm_i32_32x32 and arm64simd_mmm_i32_8x8.
+        let a = Tensor::zero::<i8>(&[m, k]).unwrap();
+        let b = Tensor::zero::<i8>(&[k, n]).unwrap();
+        let packing = &mmm.packings()[1];
+        let pa = packing.0.prepare_one(&a, 1, 0).unwrap();
+        let pb = packing.1.prepare_one(&b, 0, 1).unwrap();
+        let mut c = Tensor::zero::<i32>(&[m, n]).unwrap();
+        be.iter(move || {
+            mmm.run(
+                m,
+                n,
+                &[
+                    FusedSpec::AddMatMul {
+                        a: AsInputValue::Borrowed(&*pa),
+                        b: AsInputValue::Borrowed(&*pb),
+                        packing: 1,
+                    },
+                    FusedSpec::Store(mmm.c_view(Some(0), Some(1)).wrap(&c.view_mut())),
+                ],
+            )
+        });
+    }
+}
+
+fn bench(c: &mut Criterion) {
+    let mut g = c.benchmark_group("qmmm_i8");
+    g.sample_size(20);
+    for &shape in &[
+        (256usize, 256usize, 256usize),
+        (512, 512, 512),
+        (1024, 1024, 1024),
+        (128, 768, 768),
+        (384, 768, 768),
+        (64, 2048, 2048),
+    ] {
+        let (m, k, n) = shape;
+        g.throughput(Throughput::Elements((m * k * n) as u64));
+        g.bench_function(format!("{m}x{k}x{n}"), |be| qmmm(be, &shape));
+    }
+    g.finish();
+}
+
+criterion::criterion_group!(benches, bench);
+criterion::criterion_main!(benches);
diff --git a/linalg/benches/vnni_i32.rs b/linalg/benches/vnni_i32.rs
new file mode 100644
index 0000000000..59e6f01676
--- /dev/null
+++ b/linalg/benches/vnni_i32.rs
@@ -0,0 +1,63 @@
+#![allow(dead_code)]
+// Kernel-level benchmark: AVX-512 VNNI int8 GEMM (avx512vnni_mmm_i32_8x8, VPDPBUSD
+// over the K=4-inner PackedI8K4 layout) vs the AVX2 int8 path (avx2_mmm_i32_8x8,
+// vpmaddubsw-style widening). Both run the i8i8 packing (index 1) over the same
+// M/K/N so the only difference is the matmul inner loop.
+use criterion::*;
+use tract_data::internal::*;
+use tract_linalg::mmm::{AsInputValue, FusedSpec, MatMatMul};
+
+fn run_kernel(be: &mut Bencher, mmm: &dyn MatMatMul, m: usize, k: usize, n: usize) {
+    let a = Tensor::zero_dt(DatumType::I8, &[m, k]).unwrap();
+    let b = Tensor::zero_dt(DatumType::I8, &[k, n]).unwrap();
+    let (pack_a, pack_b) = &mmm.packings()[1];
+    let pa = pack_a.prepare_one(&a, 1, 0).unwrap();
+    let pb = pack_b.prepare_one(&b, 0, 1).unwrap();
+    let mut scratch = unsafe { mmm.allocate_scratch_space() };
+    be.iter_custom(|iters| {
+        let mut dur = std::time::Duration::default();
+        for _ in 0..iters {
+            let t = std::time::Instant::now();
+            unsafe {
+                mmm.run_with_scratch_space(
+                    m,
+                    n,
+                    scratch.as_mut(),
+                    &[FusedSpec::AddMatMul {
+                        a: AsInputValue::Borrowed(&*pa),
+                        b: AsInputValue::Borrowed(&*pb),
+                        packing: 1,
+                    }],
+                )
+                .unwrap()
+            };
+            dur += t.elapsed();
+        }
+        dur
+    });
+}
+
+fn benches(c: &mut Criterion) {
+    if !std::is_x86_feature_detected!("avx512vnni") {
+        eprintln!("avx512vnni not available, skipping");
+        return;
+    }
+    use tract_linalg::x86_64_fma::mmm::*;
+    for &(m, k, n) in
+        &[(64usize, 256usize, 64usize), (256, 256, 256), (512, 512, 512), (1024, 1024, 64)]
+    {
+        let id = format!("{m}x{k}x{n}");
+        let mut g = c.benchmark_group("vnni_i32/packed_packed");
+        g.throughput(Throughput::Elements((m * k * n) as u64));
+        g.bench_with_input(BenchmarkId::new("avx2", &id), &(m, k, n), |b, &(m, k, n)| {
+            run_kernel(b, &*avx2_mmm_i32_8x8.mmm(), m, k, n)
+        });
+        g.bench_with_input(BenchmarkId::new("avx512vnni", &id), &(m, k, n), |b, &(m, k, n)| {
+            run_kernel(b, &*avx512vnni_mmm_i32_8x8.mmm(), m, k, n)
+        });
+        g.finish();
+    }
+}
+
+criterion_group!(g, benches);
+criterion_main!(g);
diff --git a/linalg/build.rs b/linalg/build.rs
index 9e2325815b..600a2115f6 100644
--- a/linalg/build.rs
+++ b/linalg/build.rs
@@ -37,6 +37,37 @@ fn assembler_supports_sme() -> bool {
         .is_ok()
 }
 
+// Probe whether the target assembler can encode FEAT_DotProd `sdot` (the
+// indexed int8 form used by arm64simd_mmm_i32_8x8_dot). Old binutils — notably
+// the Debian stretch aarch64 cross-toolchain in CI — predate FEAT_DotProd and
+// reject `.cpu ...+dotprod` / `sdot` outright. When the probe fails we skip the
+// SDOT kernel and the `tract_arm64_dotprod` cfg; the runtime falls back to the
+// SMLAL 8x8 i32 kernel.
+fn assembler_supports_dotprod() -> bool {
+    cc::Build::new()
+        .file("arm64/arm64simd/dummy_dotprod.S")
+        .cargo_metadata(false)
+        .cargo_warnings(false)
+        .warnings(false)
+        .try_compile("tract_dotprod_probe")
+        .is_ok()
+}
+
+// Probe whether the target assembler can encode `vpdpbusd ymm` (AVX-512 VNNI
+// with AVX-512 VL, i.e. the 256-bit form). binutils gained this in ~2.30
+// (2018); the Debian stretch toolchain ships 2.28 and rejects the mnemonic.
+// When the probe fails we skip the VNNI kernel and the `tract_avx512vnni` cfg;
+// the runtime falls back to the AVX2 i32 path.
+fn assembler_supports_avx512vnni() -> bool {
+    cc::Build::new()
+        .file("x86_64/avx512vnni/dummy_vnni.S")
+        .cargo_metadata(false)
+        .cargo_warnings(false)
+        .warnings(false)
+        .try_compile("tract_avx512vnni_probe")
+        .is_ok()
+}
+
 fn include_sve() -> bool {
     // SVE/SVE2 lives on ARMv9 server/mobile cores (Neoverse V1+/N2+, Cortex-X2+,
     // Graviton 3/4) — Linux aarch64. No Apple silicon has SVE.
@@ -130,10 +161,19 @@ fn main() {
     println!("cargo:rustc-check-cfg=cfg(tract_sme)");
     // Set below only when include_sve() and the SVE compiler probe both pass.
     println!("cargo:rustc-check-cfg=cfg(tract_sve)");
+    // Set below only when the aarch64 assembler probe for `sdot` passes.
+    println!("cargo:rustc-check-cfg=cfg(tract_arm64_dotprod)");
+    // Set below only when the x86_64 assembler probe for vpdpbusd ymm passes.
+    println!("cargo:rustc-check-cfg=cfg(tract_avx512vnni)");
 
     match arch.as_ref() {
         "x86_64" => {
             let mut files = preprocess_files("x86_64/fma", &[], &suffix, false);
+            // The VNNI kernel is compiled separately (conditional on a probe) to
+            // avoid breaking old assemblers. Remove it from the main file list.
+            files.retain(|f| {
+                !f.file_name().and_then(|n| n.to_str()).map_or(false, |n| n.contains("avx512vnni"))
+            });
             files.extend(preprocess_files("x86_64/avx512", &[], &suffix, false));
 
             if os == "windows" {
@@ -184,6 +224,20 @@ fn main() {
             } else {
                 cc::Build::new().files(files).flag("-mfma").compile("x86_64_fma");
             }
+            // VNNI kernel compiled separately so old assemblers (binutils < 2.30,
+            // e.g. Debian stretch) that can't encode `vpdpbusd ymm` don't break
+            // the whole x86_64 build. The `tract_avx512vnni` cfg gates the
+            // matching Rust extern declarations and dispatch registration.
+            //
+            // The template stays in x86_64/fma/ (alongside dispatcher.j2 and the
+            // other partials it includes) so the jinja env can resolve its includes.
+            if assembler_supports_avx512vnni() {
+                let tmpl = path::Path::new("x86_64/fma/avx512vnni_mmm_i32_8x8.S.j2");
+                let out = out_dir.join(format!("avx512vnni_mmm_i32_8x8_{suffix}.S"));
+                preprocess_file(tmpl, &out, &[], &suffix, false);
+                cc::Build::new().file(&out).flag("-mfma").compile("x86_64_avx512vnni");
+                println!("cargo:rustc-cfg=tract_avx512vnni");
+            }
         }
         "arm" | "armv7" => {
             let files = preprocess_files("arm32/armvfpv2", &[], &suffix, false);
@@ -197,13 +251,30 @@ fn main() {
             cc::Build::new().files(files).flag("-marm").flag("-mfpu=neon").compile("armv7neon");
         }
         "aarch64" => {
-            let files = preprocess_files(
+            let mut files = preprocess_files(
                 "arm64/arm64simd",
                 &[("core", vec!["a53", "a55", "gen"])],
                 &suffix,
                 false,
             );
+            // The SDOT kernel is compiled separately (conditional on a probe) so
+            // old assemblers (binutils < 2.30, e.g. Debian stretch) that can't
+            // encode `sdot` don't break the whole arm64simd build. Remove it
+            // from the main file list.
+            files.retain(|f| {
+                !f.file_name().and_then(|n| n.to_str()).map_or(false, |n| n.contains("_dot"))
+            });
             cc::Build::new().files(files).compile("arm64simd");
+            // The template stays in arm64/arm64simd/ (alongside the jinja partials
+            // it includes) so the env can resolve its includes. The
+            // `tract_arm64_dotprod` cfg gates the matching Rust extern + dispatch.
+            if assembler_supports_dotprod() {
+                let tmpl = path::Path::new("arm64/arm64simd/arm64simd_mmm_i32_8x8_dot.S.j2");
+                let out = out_dir.join(format!("arm64simd_mmm_i32_8x8_dot_{suffix}.S"));
+                preprocess_file(tmpl, &out, &[], &suffix, false);
+                cc::Build::new().file(&out).compile("arm64simd_dot");
+                println!("cargo:rustc-cfg=tract_arm64_dotprod");
+            }
             if include_amx() {
                 let files = preprocess_files("arm64/apple_amx", &[], &suffix, false);
                 cc::Build::new().files(files).compile("appleamx");
diff --git a/linalg/src/arm64.rs b/linalg/src/arm64.rs
index 47f7cd4ccf..a3c9beb4c9 100644
--- a/linalg/src/arm64.rs
+++ b/linalg/src/arm64.rs
@@ -189,6 +189,40 @@ pub fn has_fp16() -> bool {
         || *HAS_FP16
 }
 
+// FEAT_DotProd (SDOT/UDOT), ARMv8.2. TRACT_DOTPROD_DISABLE=1 forces it off so
+// callers can A/B the SDOT kernel against the SMLAL 8x8 fallback on one binary.
+#[cfg(target_os = "macos")]
+pub fn has_dotprod() -> bool {
+    // Every Apple arm64 CPU (M1+/A11+) implements FEAT_DotProd.
+    std::env::var_os("TRACT_DOTPROD_DISABLE").is_none()
+}
+
+#[cfg(target_os = "linux")]
+pub fn has_dotprod() -> bool {
+    if std::env::var_os("TRACT_DOTPROD_DISABLE").is_some() {
+        return false;
+    }
+    // HWCAP_ASIMDDP = 1 << 20 on aarch64.
+    const HWCAP_ASIMDDP: u64 = 1 << 20;
+    const AT_HWCAP: u64 = 16;
+    unsafe extern "C" {
+        fn getauxval(t: u64) -> u64;
+    }
+    unsafe { (getauxval(AT_HWCAP) & HWCAP_ASIMDDP) != 0 }
+}
+
+#[cfg(not(any(target_os = "macos", target_os = "linux", target_os = "ios")))]
+pub fn has_dotprod() -> bool {
+    false
+}
+
+#[cfg(target_os = "ios")]
+pub fn has_dotprod() -> bool {
+    // A11+ (iPhone10,1+) implement FEAT_DotProd.
+    std::env::var_os("TRACT_DOTPROD_DISABLE").is_none()
+        && IPHONE_MODEL_MAJOR.map(|it| it >= 10).unwrap_or(false)
+}
+
 #[target_feature(enable = "fp16")]
 #[inline]
 pub unsafe fn add_f16(a: f16, b: f16) -> f16 {
@@ -351,7 +385,19 @@ pub fn plug(ops: &mut Ops) {
         arm64fp16::plug(ops);
     }
 
-    ops.qmmm_i32 = Box::new(|_, _, _| arm64simd_mmm_i32_8x8.mmm());
+    // SDOT (~4x the SMLAL 8x8) when FEAT_DotProd is present, else the SMLAL 8x8 fallback.
+    // The SDOT kernel only exists when the assembler could encode `sdot`
+    // (`tract_arm64_dotprod`, set by build.rs); otherwise always use the SMLAL 8x8.
+    #[cfg(tract_arm64_dotprod)]
+    if has_dotprod() {
+        ops.qmmm_i32 = Box::new(|_, _, _| arm64simd_mmm_i32_8x8_dot.mmm());
+    } else {
+        ops.qmmm_i32 = Box::new(|_, _, _| arm64simd_mmm_i32_8x8.mmm());
+    }
+    #[cfg(not(tract_arm64_dotprod))]
+    {
+        ops.qmmm_i32 = Box::new(|_, _, _| arm64simd_mmm_i32_8x8.mmm());
+    }
     ops.qmmv_i32 = Box::new(|_, _| arm64simd_mmm_i32_64x1.mmm());
     ops.mmv_f32 = match *KIND {
         Kind::CortexA53 => Box::new(|_, _| arm64simd_mmm_f32_64x1_a53.mmm()),
diff --git a/linalg/src/arm64/arm64simd.rs b/linalg/src/arm64/arm64simd.rs
index f90d92926f..2f3ec68389 100644
--- a/linalg/src/arm64/arm64simd.rs
+++ b/linalg/src/arm64/arm64simd.rs
@@ -84,6 +84,21 @@ MMMExternKernel!(arm64simd_mmm_i32_8x8<i32>(8, 8)@(16, 16)
    store(i8)
 );
 
+// SDOT (FEAT_DotProd) variant: 4-K reduction per instruction (~4x the SMLAL
+// 8x8 above). Uses the K=4-inner PackedI8K4 packing; identical v16..v31 tile
+// layout, so it reuses all the i32 fuse/store/q_scale machinery.
+//
+// Gated on `tract_arm64_dotprod` (set by build.rs when the assembler can encode
+// `sdot`; binutils < 2.30 cannot). On old toolchains the kernel is omitted and
+// dispatch falls back to the SMLAL 8x8 i32 kernel.
+#[cfg(tract_arm64_dotprod)]
+MMMExternKernel!(arm64simd_mmm_i32_8x8_dot<i32>(8, 8)@(16, 16)
+   where(super::has_dotprod)
+   packing[1] = i8i8 => |k| k.with_packing(crate::pack::PackedI8K4::new(8), crate::pack::PackedI8K4::new(8));
+   quality(ManuallyOptimized)
+   store(i8)
+);
+
 MMMExternKernel!(arm64simd_mmm_i32_64x1<i32>(64, 1)@(16, 1)
    packing[1] = i8i8 => |k| k.with_packing(PackedFormat::new(DatumType::I8, 64,16), PackedFormat::new(DatumType::I8, 1, 1));
    quality(ManuallyOptimized)
@@ -112,6 +127,8 @@ pub fn plug(ops: &mut Ops) {
         arm64simd_mmm_i32_8x8.mmm(),
         arm64simd_mmm_i32_64x1.mmm(),
     ]);
+    #[cfg(tract_arm64_dotprod)]
+    ops.mmm_impls.push(arm64simd_mmm_i32_8x8_dot.mmm());
     panel_extract::plug(ops);
 }
 
diff --git a/linalg/src/frame/mmm/mod.rs b/linalg/src/frame/mmm/mod.rs
index bbe84cf8b9..bafc69826e 100644
--- a/linalg/src/frame/mmm/mod.rs
+++ b/linalg/src/frame/mmm/mod.rs
@@ -217,10 +217,19 @@ impl<K: MatMatMulKer> MatMatMul for K {
                         prefer_row = (!col) as usize;
                     }
                 }
+                // k drives the single-thread cache-block size; read it from the
+                // first AddMatMul's packed input (0 if none → max block).
+                let k = non_linear
+                    .iter()
+                    .find_map(|f| match f {
+                        FusedSpec::AddMatMul { a, .. } => Some(a.k()),
+                        _ => None,
+                    })
+                    .unwrap_or(0);
                 if prefer_col > prefer_row {
-                    run_with_scratch_space_col_outer(self, m, n, scratch, non_linear)
+                    run_with_scratch_space_col_outer(self, m, n, k, scratch, non_linear)
                 } else {
-                    run_with_scratch_space_row_outer(self, m, n, scratch, non_linear)
+                    run_with_scratch_space_row_outer(self, m, n, k, scratch, non_linear)
                 }
             }
         }
@@ -270,23 +279,153 @@ unsafe fn run_with_scratch_space_vec<K: MatMatMulKer>(
     }
 }
 
+/// Upper bound on the single-thread panel-block edge (matches the multithread
+/// `chunk_grid` default).
+const ST_BLK_MAX: usize = 16;
+
+#[cfg(target_os = "linux")]
+fn parse_cache_size(s: &str) -> usize {
+    let s = s.trim();
+    let (num, mult) = if let Some(n) = s.strip_suffix(['K', 'k']) {
+        (n, 1024)
+    } else if let Some(n) = s.strip_suffix(['M', 'm']) {
+        (n, 1024 * 1024)
+    } else {
+        (s, 1)
+    };
+    num.trim().parse::<usize>().unwrap_or(0) * mult
+}
+
+/// Best-effort L2 data-cache size in bytes (per perf-core / cluster); 0 if
+/// unknown. Cached. Used to size the single-thread cache-block budget so it is
+/// correct across hardware instead of a hard-coded constant.
+fn detect_l2_bytes() -> usize {
+    static L2: std::sync::OnceLock<usize> = std::sync::OnceLock::new();
+    *L2.get_or_init(|| {
+        #[cfg(target_os = "macos")]
+        {
+            let sysctl = |k: &str| -> Option<usize> {
+                let o = std::process::Command::new("sysctl").arg("-n").arg(k).output().ok()?;
+                if !o.status.success() {
+                    return None;
+                }
+                String::from_utf8_lossy(&o.stdout).trim().parse().ok()
+            };
+            // Prefer the performance-core L2 on hybrid Apple Silicon.
+            sysctl("hw.perflevel0.l2cachesize").or_else(|| sysctl("hw.l2cachesize")).unwrap_or(0)
+        }
+        #[cfg(target_os = "linux")]
+        {
+            // index2/index3 is typically the unified L2 (index0/1 are L1 d/i).
+            for idx in [2usize, 3] {
+                if let Ok(s) = std::fs::read_to_string(format!(
+                    "/sys/devices/system/cpu/cpu0/cache/index{idx}/size"
+                )) {
+                    let b = parse_cache_size(s.trim());
+                    if b > 0 {
+                        return b;
+                    }
+                }
+            }
+            0
+        }
+        #[cfg(not(any(target_os = "macos", target_os = "linux")))]
+        {
+            0
+        }
+    })
+}
+
+/// Working-set budget (bytes) for the single-thread cache-block: ~a third of L2
+/// (leaving room for the C accumulator tile + packing metadata). Conservative
+/// 256 KiB fallback when L2 is unknown (WASM/Windows/BSD) ⇒ small blocks ≈ the
+/// naive loop, so it can never over-block a cache it can't see.
+fn block_budget_bytes() -> usize {
+    let l2 = detect_l2_bytes();
+    if l2 == 0 { 256 * 1024 } else { (l2 / 3).clamp(64 * 1024, 8 * 1024 * 1024) }
+}
+
+/// Cache-adaptive panel-block edge: large enough to amortise streaming, small
+/// enough that the block's A+B sub-panels (`~blk·(mr+nr)·k·elem_bytes`) stay
+/// L2-resident at the given `k`. Capped at [`ST_BLK_MAX`]; the floor of 1
+/// degrades exactly to the naive loop, so an unknown/small cache can never
+/// over-block (regression-safe). The budget is **cache-size derived** (not a
+/// hard-coded constant), so it is correct across hardware.
+#[inline]
+fn st_block_edge(mr: usize, nr: usize, k: usize, elem_bytes: usize) -> usize {
+    if k == 0 {
+        return ST_BLK_MAX;
+    }
+    let per_blk = ((mr + nr) * k * elem_bytes.max(1)).max(1);
+    (block_budget_bytes() / per_blk).clamp(1, ST_BLK_MAX)
+}
+
+/// Single-thread tile walk over the `m_panels × n_panels` grid, blocked into
+/// cache-sized panel blocks for locality (the naive nested loop re-streams the
+/// whole inner operand per outer panel at large k; the multithread path already
+/// blocks this way via `chunk_grid`). `col_outer` selects the within-block inner
+/// order (B-reuse vs A-reuse). Reordering independent tiles changes no result —
+/// bit-exact with the naive loop.
+#[inline]
+unsafe fn run_single_thread_blocked<K: MatMatMulKer>(
+    ker: &K,
+    m_panels: usize,
+    n_panels: usize,
+    k: usize,
+    col_outer: bool,
+    scratch: &mut ScratchSpaceImpl<K::Acc>,
+    non_linear: &[FusedSpec],
+) -> TractResult<()> {
+    unsafe {
+        let blk = st_block_edge(ker.mr(), ker.nr(), k, K::Acc::datum_type().size_of());
+        scratch.run_in_tls_scope(|scratch, tls| {
+            let mut jb = 0;
+            while jb < n_panels {
+                let jb_end = (jb + blk).min(n_panels);
+                let mut ja = 0;
+                while ja < m_panels {
+                    let ja_end = (ja + blk).min(m_panels);
+                    if col_outer {
+                        for ib in jb..jb_end {
+                            for ia in ja..ja_end {
+                                scratch.run_one_tile(ker, non_linear, tls, ia, ib)?;
+                            }
+                        }
+                    } else {
+                        for ia in ja..ja_end {
+                            for ib in jb..jb_end {
+                                scratch.run_one_tile(ker, non_linear, tls, ia, ib)?;
+                            }
+                        }
+                    }
+                    ja = ja_end;
+                }
+                jb = jb_end;
+            }
+            TractResult::Ok(())
+        })
+    }
+}
+
 unsafe fn run_with_scratch_space_col_outer<K: MatMatMulKer>(
     ker: &K,
     m: usize,
     n: usize,
+    k: usize,
     scratch: &mut ScratchSpaceImpl<K::Acc>,
     non_linear: &[FusedSpec],
 ) -> TractResult<()> {
     unsafe {
         match crate::multithread::current_tract_executor() {
-            Executor::SingleThread => scratch.run_in_tls_scope(|scratch, tls| {
-                for ib in 0..n.divceil(ker.nr()) {
-                    for ia in 0..m.divceil(ker.mr()) {
-                        scratch.run_one_tile(ker, non_linear, tls, ia, ib)?;
-                    }
-                }
-                TractResult::Ok(())
-            }),
+            Executor::SingleThread => run_single_thread_blocked(
+                ker,
+                m.divceil(ker.mr()),
+                n.divceil(ker.nr()),
+                k,
+                true,
+                scratch,
+                non_linear,
+            ),
             #[cfg(feature = "multithread-mm")]
             Executor::MultiThread(pool) => chunked_dispatch_rayon(
                 Some(&pool),
@@ -327,19 +466,21 @@ unsafe fn run_with_scratch_space_row_outer<K: MatMatMulKer>(
     ker: &K,
     m: usize,
     n: usize,
+    k: usize,
     scratch: &mut ScratchSpaceImpl<K::Acc>,
     non_linear: &[FusedSpec],
 ) -> TractResult<()> {
     unsafe {
         match crate::multithread::current_tract_executor() {
-            Executor::SingleThread => scratch.run_in_tls_scope(|scratch, tls| {
-                for ia in 0..m.divceil(ker.mr()) {
-                    for ib in 0..n.divceil(ker.nr()) {
-                        scratch.run_one_tile(ker, non_linear, tls, ia, ib)?;
-                    }
-                }
-                TractResult::Ok(())
-            }),
+            Executor::SingleThread => run_single_thread_blocked(
+                ker,
+                m.divceil(ker.mr()),
+                n.divceil(ker.nr()),
+                k,
+                false,
+                scratch,
+                non_linear,
+            ),
             #[cfg(feature = "multithread-mm")]
             Executor::MultiThread(pool) => chunked_dispatch_rayon(
                 Some(&pool),
diff --git a/linalg/src/frame/mmm/tests/packed_packed.rs b/linalg/src/frame/mmm/tests/packed_packed.rs
index 8437990c72..ff27833aa6 100644
--- a/linalg/src/frame/mmm/tests/packed_packed.rs
+++ b/linalg/src/frame/mmm/tests/packed_packed.rs
@@ -379,3 +379,43 @@ impl<K: MatMatMulKer> PackedPackedProblem<K> {
         result
     }
 }
+
+// Large-shape frame tests that exercise the single-thread 2D-blocked tile walk
+// (`run_single_thread_blocked`): the existing `arbitrary_problem` frame proptests
+// only reach 3 panels per dim (m,n < 3·mr), below the ST_BLK=16 blocking
+// threshold, so the blocked path was otherwise uncovered. generic_f32_4x4 has
+// mr=nr=4, so m,n=80 → 20×20 panels → multiple blocks. Compares the frame
+// output against the naive reference (must be bit/approx-exact).
+#[cfg(test)]
+mod single_thread_blocking {
+    use super::PackedPackedProblem;
+    use crate::generic::mmm::generic_f32_4x4;
+    use tract_data::internal::TractResult;
+
+    fn check_large(m: usize, n: usize, k: usize) -> TractResult<()> {
+        let a: Vec<f32> = (0..m * k).map(|i| ((i * 7 + 3) % 13) as f32 - 6.0).collect();
+        let b: Vec<f32> = (0..k * n).map(|i| ((i * 5 + 1) % 11) as f32 - 5.0).collect();
+        PackedPackedProblem::frame(&*generic_f32_4x4, 0, m, n, a, b).check()
+    }
+
+    #[test]
+    fn blocked_80x80() -> TractResult<()> {
+        check_large(80, 80, 24) // 20×20 panels, multiple ST_BLK blocks
+    }
+    #[test]
+    fn blocked_skew_200x40() -> TractResult<()> {
+        check_large(200, 40, 8) // 50×10 panels (m-axis chunked)
+    }
+    #[test]
+    fn blocked_40x200() -> TractResult<()> {
+        check_large(40, 200, 8) // 10×50 panels (n-axis chunked)
+    }
+    #[test]
+    fn blocked_64x64_exact() -> TractResult<()> {
+        check_large(64, 64, 16) // exactly 16×16 panels (block boundary)
+    }
+    #[test]
+    fn blocked_68x68_offset() -> TractResult<()> {
+        check_large(68, 68, 10) // 17×17 panels (one full block + a 1-panel remainder)
+    }
+}
diff --git a/linalg/src/x86_64_fma.rs b/linalg/src/x86_64_fma.rs
index 733d1e7121..7b042d5199 100644
--- a/linalg/src/x86_64_fma.rs
+++ b/linalg/src/x86_64_fma.rs
@@ -5,6 +5,7 @@ use crate::x86_64_fma::softmax::x86_64_fma_softmax2_fastcompact_f32_32n;
 
 pub mod mmm;
 
+pub mod act;
 pub mod by_scalar;
 mod intel;
 pub mod max;
@@ -14,10 +15,18 @@ pub mod softmax;
 const AVX2: fn() -> bool = || is_x86_feature_detected!("avx2");
 const FMA: fn() -> bool = || is_x86_feature_detected!("fma");
 const AVX512F: fn() -> bool = || is_x86_feature_detected!("avx512f");
+#[cfg(tract_avx512vnni)]
+const AVX512VNNI: fn() -> bool = || is_x86_feature_detected!("avx512vnni");
 
 tanh_impl!(f32, fma_tanh_f32, 8, 8, is_x86_feature_detected!("fma"));
 sigmoid_impl!(f32, fma_sigmoid_f32, 8, 8, is_x86_feature_detected!("fma"));
 
+// AVX-512 (zmm, 16-wide) variants. The assembly lives in x86_64/avx512/; the
+// main loop handles 64 lanes (4 zmm) per iteration with a 16-lane tail, so
+// nr()=16 (any multiple of 16 is safe).
+tanh_impl!(f32, avx512_tanh_f32, 16, 16, is_x86_feature_detected!("avx512f"));
+sigmoid_impl!(f32, avx512_sigmoid_f32, 16, 16, is_x86_feature_detected!("avx512f"));
+
 fn plug_avx2(_ops: &mut Ops) {}
 
 fn plug_fma(ops: &mut Ops) {
@@ -33,7 +42,19 @@ fn plug_fma(ops: &mut Ops) {
     log::info!("sigmoid_f32, tanh_f32: x86_64/fma activated");
 }
 
-fn plug_avx512f(_ops: &mut Ops) {}
+fn plug_avx512f(ops: &mut Ops) {
+    ops.sigmoid_f32 = Box::new(|| avx512_sigmoid_f32::ew());
+    ops.tanh_f32 = Box::new(|| avx512_tanh_f32::ew());
+    ops.hardswish_f32 = Box::new(|| act::x86_64_avx512_hardswish_f32_64n::ew());
+    ops.leaky_relu_f32 = Box::new(|| act::x86_64_avx512_leaky_relu_f32_64n::ew());
+    ops.silu_f32 = Box::new(|| act::x86_64_avx512_silu_f32_16n::ew());
+    ops.gelu_f32 = Box::new(|| act::x86_64_avx512_gelu_f32_16n::ew());
+
+    log::info!(
+        "sigmoid_f32, tanh_f32, hardswish_f32, leaky_relu_f32, \
+         silu_f32, gelu_f32: x86_64/avx512f activated"
+    );
+}
 
 pub fn plug(ops: &mut Ops) {
     mmm::plug(ops);
diff --git a/linalg/src/x86_64_fma/act.rs b/linalg/src/x86_64_fma/act.rs
new file mode 100644
index 0000000000..1acf995655
--- /dev/null
+++ b/linalg/src/x86_64_fma/act.rs
@@ -0,0 +1,258 @@
+// AVX-512 (zmm, 16-wide) element-wise activation kernels with no FMA
+// predecessor on x86: hardswish and leaky_relu. They mirror the aarch64 NEON
+// kernels (arm64simd_hardswish_f32_8n / arm64simd_leaky_relu_f32_8n) but use
+// 512-bit zmm registers, processing 64 f32 lanes per iteration. Validated
+// against the generic scalar reference via the *_frame_tests! macros.
+
+// hardswish(x) = x * relu6(x + 3) / 6
+//              = x * max(0, min(6, x + 3)) * (1/6)
+ew_impl_wrap!(
+    f32,
+    x86_64_avx512_hardswish_f32_64n,
+    64,
+    16,
+    (),
+    #[inline(never)]
+    fn run(buf: &mut [f32], _: ()) {
+        debug_assert!(buf.len() % Self::nr() == 0);
+        debug_assert!(buf.as_ptr() as usize % Self::alignment_bytes() == 0);
+        if buf.is_empty() {
+            return;
+        }
+        unsafe { x86_64_avx512_hardswish_f32_64n_run(buf) }
+    }
+);
+
+#[target_feature(enable = "avx512f")]
+unsafe fn x86_64_avx512_hardswish_f32_64n_run(buf: &mut [f32]) {
+    unsafe {
+        let len = buf.len();
+        let ptr = buf.as_ptr();
+        std::arch::asm!("
+            vbroadcastss zmm0, xmm0          // 3.0
+            vbroadcastss zmm1, xmm1          // 6.0
+            vbroadcastss zmm2, xmm2          // 1/6
+            vpxord       zmm3, zmm3, zmm3    // 0.0
+            2:
+                vmovaps zmm4, [{ptr}]
+                vmovaps zmm5, [{ptr} + 64]
+                vmovaps zmm6, [{ptr} + 128]
+                vmovaps zmm7, [{ptr} + 192]
+
+                vaddps  zmm8,  zmm4, zmm0
+                vaddps  zmm9,  zmm5, zmm0
+                vaddps  zmm10, zmm6, zmm0
+                vaddps  zmm11, zmm7, zmm0
+
+                vminps  zmm8,  zmm8,  zmm1
+                vminps  zmm9,  zmm9,  zmm1
+                vminps  zmm10, zmm10, zmm1
+                vminps  zmm11, zmm11, zmm1
+
+                vmaxps  zmm8,  zmm8,  zmm3
+                vmaxps  zmm9,  zmm9,  zmm3
+                vmaxps  zmm10, zmm10, zmm3
+                vmaxps  zmm11, zmm11, zmm3
+
+                vmulps  zmm8,  zmm8,  zmm4
+                vmulps  zmm9,  zmm9,  zmm5
+                vmulps  zmm10, zmm10, zmm6
+                vmulps  zmm11, zmm11, zmm7
+
+                vmulps  zmm8,  zmm8,  zmm2
+                vmulps  zmm9,  zmm9,  zmm2
+                vmulps  zmm10, zmm10, zmm2
+                vmulps  zmm11, zmm11, zmm2
+
+                vmovaps [{ptr}],       zmm8
+                vmovaps [{ptr} + 64],  zmm9
+                vmovaps [{ptr} + 128], zmm10
+                vmovaps [{ptr} + 192], zmm11
+
+                add {ptr}, 256
+                sub {len}, 64
+                jnz 2b
+            ",
+        len = inout(reg) len => _,
+        ptr = inout(reg) ptr => _,
+        inout("xmm0") 3.0f32 => _,
+        inout("xmm1") 6.0f32 => _,
+        inout("xmm2") 1.0f32 / 6.0f32 => _,
+        out("zmm3") _,
+        out("zmm4") _, out("zmm5") _, out("zmm6") _, out("zmm7") _,
+        out("zmm8") _, out("zmm9") _, out("zmm10") _, out("zmm11") _,
+        );
+    }
+}
+
+#[cfg(test)]
+pub mod test_x86_64_avx512_hardswish_f32_64n {
+    use super::*;
+    hardswish_frame_tests!(
+        is_x86_feature_detected!("avx512f"),
+        f32,
+        x86_64_avx512_hardswish_f32_64n
+    );
+}
+
+// leaky_relu(x) = x > 0 ? x : alpha * x
+ew_impl_wrap!(
+    f32,
+    x86_64_avx512_leaky_relu_f32_64n,
+    64,
+    16,
+    f32,
+    #[inline(never)]
+    fn run(buf: &mut [f32], alpha: f32) {
+        debug_assert!(buf.len() % Self::nr() == 0);
+        debug_assert!(buf.as_ptr() as usize % Self::alignment_bytes() == 0);
+        if buf.is_empty() {
+            return;
+        }
+        unsafe { x86_64_avx512_leaky_relu_f32_64n_run(buf, alpha) }
+    }
+);
+
+#[target_feature(enable = "avx512f")]
+unsafe fn x86_64_avx512_leaky_relu_f32_64n_run(buf: &mut [f32], alpha: f32) {
+    unsafe {
+        let len = buf.len();
+        let ptr = buf.as_ptr();
+        std::arch::asm!("
+            vbroadcastss zmm0, xmm0          // alpha
+            vpxord       zmm1, zmm1, zmm1    // 0.0
+            2:
+                vmovaps zmm4, [{ptr}]
+                vmovaps zmm5, [{ptr} + 64]
+                vmovaps zmm6, [{ptr} + 128]
+                vmovaps zmm7, [{ptr} + 192]
+
+                // alpha * x in zmm8..11
+                vmulps  zmm8,  zmm4, zmm0
+                vmulps  zmm9,  zmm5, zmm0
+                vmulps  zmm10, zmm6, zmm0
+                vmulps  zmm11, zmm7, zmm0
+
+                // mask = x > 0
+                vcmpps  k1, zmm4, zmm1, 14
+                vcmpps  k2, zmm5, zmm1, 14
+                vcmpps  k3, zmm6, zmm1, 14
+                vcmpps  k4, zmm7, zmm1, 14
+
+                // where x > 0, overwrite alpha*x with x
+                vmovaps zmm8{{k1}},  zmm4
+                vmovaps zmm9{{k2}},  zmm5
+                vmovaps zmm10{{k3}}, zmm6
+                vmovaps zmm11{{k4}}, zmm7
+
+                vmovaps [{ptr}],       zmm8
+                vmovaps [{ptr} + 64],  zmm9
+                vmovaps [{ptr} + 128], zmm10
+                vmovaps [{ptr} + 192], zmm11
+
+                add {ptr}, 256
+                sub {len}, 64
+                jnz 2b
+            ",
+        len = inout(reg) len => _,
+        ptr = inout(reg) ptr => _,
+        inout("xmm0") alpha => _,
+        out("zmm1") _,
+        out("zmm4") _, out("zmm5") _, out("zmm6") _, out("zmm7") _,
+        out("zmm8") _, out("zmm9") _, out("zmm10") _, out("zmm11") _,
+        out("k1") _, out("k2") _, out("k3") _, out("k4") _,
+        );
+    }
+}
+
+#[cfg(test)]
+pub mod test_x86_64_avx512_leaky_relu_f32_64n {
+    use super::*;
+    leaky_relu_frame_tests!(
+        is_x86_feature_detected!("avx512f"),
+        f32,
+        x86_64_avx512_leaky_relu_f32_64n
+    );
+}
+
+// SiLU(x) = x * sigmoid(x). Composed at the kernel level (mirrors arm64): save
+// the input chunk, run the AVX-512 sigmoid kernel in place, then multiply back
+// by the saved original. nr() and CHUNK (256) are multiples of 16 so the
+// sigmoid kernel always receives a 64-byte-aligned slice whose length is a
+// multiple of 16.
+ew_impl_wrap!(
+    f32,
+    x86_64_avx512_silu_f32_16n,
+    16,
+    16,
+    (),
+    #[inline(never)]
+    fn run(buf: &mut [f32], _: ()) {
+        debug_assert!(buf.len() % Self::nr() == 0);
+        debug_assert!(buf.as_ptr() as usize % Self::alignment_bytes() == 0);
+        const CHUNK: usize = 256;
+        let mut scratch = [0f32; CHUNK];
+        let mut start = 0;
+        while start < buf.len() {
+            let end = (start + CHUNK).min(buf.len());
+            let chunk = &mut buf[start..end];
+            let n = chunk.len();
+            scratch[..n].copy_from_slice(chunk);
+            super::avx512_sigmoid_f32::run(chunk, ());
+            for i in 0..n {
+                chunk[i] *= scratch[i];
+            }
+            start = end;
+        }
+    }
+);
+
+#[cfg(test)]
+pub mod test_x86_64_avx512_silu_f32_16n {
+    use super::*;
+    silu_frame_tests!(is_x86_feature_detected!("avx512f"), f32, x86_64_avx512_silu_f32_16n);
+}
+
+// Tanh-form GELU (pow=3) matching tract's GeluApproximate:
+//   gelu(x) = 0.5 * x * (1 + tanh(sqrt(2/pi) * (x + 0.044715 * x^3)))
+// Composed at the kernel level (mirrors arm64): save the original x, compute
+// the tanh argument in place, run the AVX-512 tanh kernel, then finish with the
+// 0.5 * x * (1 + tanh) combine.
+ew_impl_wrap!(
+    f32,
+    x86_64_avx512_gelu_f32_16n,
+    16,
+    16,
+    (),
+    #[inline(never)]
+    fn run(buf: &mut [f32], _: ()) {
+        debug_assert!(buf.len() % Self::nr() == 0);
+        debug_assert!(buf.as_ptr() as usize % Self::alignment_bytes() == 0);
+        const SQRT_2_OVER_PI: f32 = 0.7978845608028654;
+        const COEF: f32 = 0.044715;
+        const CHUNK: usize = 256;
+        let mut scratch = [0f32; CHUNK];
+        let mut start = 0;
+        while start < buf.len() {
+            let end = (start + CHUNK).min(buf.len());
+            let chunk = &mut buf[start..end];
+            let n = chunk.len();
+            for i in 0..n {
+                let x = chunk[i];
+                scratch[i] = x;
+                chunk[i] = SQRT_2_OVER_PI * (x + COEF * x * x * x);
+            }
+            super::avx512_tanh_f32::run(chunk, ());
+            for i in 0..n {
+                chunk[i] = 0.5 * scratch[i] * (1.0 + chunk[i]);
+            }
+            start = end;
+        }
+    }
+);
+
+#[cfg(test)]
+pub mod test_x86_64_avx512_gelu_f32_16n {
+    use super::*;
+    gelu_frame_tests!(is_x86_feature_detected!("avx512f"), f32, x86_64_avx512_gelu_f32_16n);
+}
diff --git a/linalg/src/x86_64_fma/mmm.rs b/linalg/src/x86_64_fma/mmm.rs
index 7b094ac2e9..eaaf40b9d0 100644
--- a/linalg/src/x86_64_fma/mmm.rs
+++ b/linalg/src/x86_64_fma/mmm.rs
@@ -2,7 +2,7 @@ use crate::Ops;
 use crate::block_quant::*;
 use crate::mmm::ImplementationQuality::ManuallyOptimized;
 use crate::mmm::MatMatMul;
-use crate::pack::PackedFormat;
+use crate::pack::{PackedFormat, PackedI8K4};
 
 use super::*;
 
@@ -91,6 +91,22 @@ MMMExternKernel! { avx2_mmm_i32_8x8<i32>(8,8)@(256,4) where(AVX2)
     store(i8)
 }
 
+// AVX-512 VNNI int8 GEMM: same 8x8 column-accumulator tile and quantization
+// epilogue as avx2_mmm_i32_8x8, but the i8i8 matmul inner loop uses VPDPBUSD
+// (4-way K dot) over the K=4-inner PackedI8K4 layout. VPDPBUSD is u8*s8, so the
+// kernel offsets A by +128 and removes the 128*sum_k(B) bias per column before
+// the epilogue, making the i32 accumulators bit-identical to the AVX2 path.
+//
+// Gated on `tract_avx512vnni` (set by build.rs when the assembler can encode
+// `vpdpbusd ymm`; binutils < 2.30 cannot). On old toolchains the kernel is
+// omitted entirely and the AVX2 i32 path is used instead.
+#[cfg(tract_avx512vnni)]
+MMMExternKernel! { avx512vnni_mmm_i32_8x8<i32>(8,8)@(256,4) where(AVX512VNNI)
+    packing[1] = i8i8 => |k| k.with_packing(PackedI8K4::new(8), PackedI8K4::new(8));
+    quality(ManuallyOptimized)
+    store(i8)
+}
+
 pub fn plug(ops: &mut Ops) {
     if is_x86_feature_detected!("avx2") {
         plug_avx2(ops);
@@ -98,11 +114,22 @@ pub fn plug(ops: &mut Ops) {
             plug_fma(ops);
             if is_x86_feature_detected!("avx512f") {
                 plug_avx512f(ops);
+                #[cfg(tract_avx512vnni)]
+                if is_x86_feature_detected!("avx512vnni") {
+                    plug_avx512vnni(ops);
+                }
             }
         }
     }
 }
 
+#[cfg(tract_avx512vnni)]
+pub fn plug_avx512vnni(ops: &mut Ops) {
+    ops.mmm_impls.push(avx512vnni_mmm_i32_8x8.mmm());
+    ops.qmmm_i32 = Box::new(|_, _, _| avx512vnni_mmm_i32_8x8.mmm());
+    log::info!("qmmm_i32: x86_64/avx512vnni activated");
+}
+
 pub fn plug_avx2(ops: &mut Ops) {
     ops.mmm_impls.push(mmm::avx2_mmm_i32_8x8.mmm());
     ops.qmmm_i32 = Box::new(|_, _, _| mmm::avx2_mmm_i32_8x8.mmm());
diff --git a/linalg/x86_64/avx512/sigmoid_f32.S.j2 b/linalg/x86_64/avx512/sigmoid_f32.S.j2
index 9b0c3c9df1..bc57bbb8c5 100644
--- a/linalg/x86_64/avx512/sigmoid_f32.S.j2
+++ b/linalg/x86_64/avx512/sigmoid_f32.S.j2
@@ -1,8 +1,9 @@
 {#
 // vim: set syntax=asm :
 
-
-// TODO[TSolberg] : Not validated.
+// AVX-512 (zmm, 16-wide) sigmoid. Uses a rational (Padé-style) approximation
+// of sigmoid clamped to [-18, 18]. Validated against the generic scalar
+// reference via sigmoid_frame_tests! (see x86_64_fma.rs).
 
 System V ABI:
     args: rdi, rsi, rdx, rcx, r8, r9
@@ -89,7 +90,7 @@ avx512_sigmoid_f32_{{suffix}} proc
     cmp     rsi, 0
     je      {{L}}done
 
-    cmp     rsi, 32
+    cmp     rsi, 64
     jl      {{L}}loop_1
 
 {{L}}loop_4:
@@ -194,8 +195,8 @@ avx512_sigmoid_f32_{{suffix}} proc
     vmovaps [rdi + 192], zmm7
 
     add     rdi, 256
-    sub     rsi, 32
-    cmp     rsi, 32
+    sub     rsi, 64
+    cmp     rsi, 64
     jg      {{L}}loop_4
 
     cmp     rsi, 0
@@ -243,8 +244,8 @@ avx512_sigmoid_f32_{{suffix}} proc
     vaddps          zmm4, zmm4, zmm1
 
     vmovaps [rdi], zmm4
-    add     rdi, 32
-    sub     rsi, 8
+    add     rdi, 64
+    sub     rsi, 16
     jnz     {{L}}loop_1
 
 {{L}}done:
diff --git a/linalg/x86_64/avx512/tanh_f32.S.j2 b/linalg/x86_64/avx512/tanh_f32.S.j2
index 65e01bd029..dd0325b201 100644
--- a/linalg/x86_64/avx512/tanh_f32.S.j2
+++ b/linalg/x86_64/avx512/tanh_f32.S.j2
@@ -1,7 +1,9 @@
 {#
 // vim: set syntax=asm :
 
-// TODO[TSolberg] : Not validated.
+// AVX-512 (zmm, 16-wide) tanh. Polynomial-numerator / polynomial-denominator
+// rational approximation of tanh clamped to [-9, 9]. Validated against the
+// generic scalar reference via tanh_frame_tests! (see x86_64_fma.rs).
 
 System V ABI:
     args: rdi, rsi, rdx, rcx, r8, r9
@@ -88,7 +90,7 @@ avx512_tanh_f32_{{suffix}} proc
     cmp     rsi, 0
     je      {{L}}done
 
-    cmp     rsi, 32
+    cmp     rsi, 64
     jl      {{L}}loop_1
 
 {{L}}loop_4:
@@ -188,8 +190,8 @@ avx512_tanh_f32_{{suffix}} proc
     vmovaps [rdi + 192], zmm7
 
     add     rdi, 256
-    sub     rsi, 32
-    cmp     rsi, 32
+    sub     rsi, 64
+    cmp     rsi, 64
     jg      {{L}}loop_4
 
     cmp     rsi, 0
@@ -235,8 +237,8 @@ avx512_tanh_f32_{{suffix}} proc
     vdivps          zmm4, zmm4, zmm12
 
     vmovaps [rdi], zmm4
-    add     rdi, 32
-    sub     rsi, 8
+    add     rdi, 64
+    sub     rsi, 16
     jnz     {{L}}loop_1
 
 {{L}}done:
diff --git a/linalg/x86_64/avx512vnni/dummy_vnni.S b/linalg/x86_64/avx512vnni/dummy_vnni.S
new file mode 100644
index 0000000000..293f07fd4c
--- /dev/null
+++ b/linalg/x86_64/avx512vnni/dummy_vnni.S
@@ -0,0 +1,13 @@
+// Build-time capability probe for the assembler, used by build.rs
+// (assembler_supports_avx512vnni). Older binutils — notably the Debian stretch
+// x86_64 toolchain in CI — predate AVX-512 VNNI (added in binutils ~2.30) and
+// cannot assemble `vpdpbusd ymm` even when targeting a VNNI-capable CPU. If
+// this file fails to assemble, build.rs skips the VNNI kernel and the
+// `tract_avx512vnni` cfg, and the runtime falls back to the AVX2 i32 path.
+// Not linked into anything.
+.intel_syntax noprefix
+.text
+.globl tract_avx512vnni_probe
+tract_avx512vnni_probe:
+    vpdpbusd ymm0, ymm1, ymm2
+    ret
diff --git a/linalg/x86_64/fma/avx512vnni_mmm_i32_8x8.S.j2 b/linalg/x86_64/fma/avx512vnni_mmm_i32_8x8.S.j2
new file mode 100644
index 0000000000..ed5d4540af
--- /dev/null
+++ b/linalg/x86_64/fma/avx512vnni_mmm_i32_8x8.S.j2
@@ -0,0 +1,676 @@
+{#
+// vim: set syntax=asm :
+
+/* mmm 8x8:
+
+    ymm0 ymm1 ymm2 ymm3 ymm4 ymm5 ymm6 ymm7
+
+System V ABI:
+    args: rdi, rsi, rdx, rcx, r8, r9
+    preserve: rbx, rsp, rbp, r12, r13, r14, r15
+    scratch: rax, rdi, rsi, rdx, rcx, r8, r9, r10, r11
+    return: rax (+rdx)
+
+Windows ABI:
+    args: RCX, RDX, R8, R9
+    preserve: RBX, RBP, RDI, RSI, RSP, R12, R13, R14, R15, and XMM6-15
+    scratch: RAX, RCX, RDX, R8, R9, R10, R11, XMM0-5, and the upper portions of YMM0-15 and ZMM0-15
+    return: rax (+rdx)
+*/
+#}
+
+{% if msvc %}
+
+_text segment
+avx512vnni_mmm_i32_8x8_{{suffix}} proc
+
+{% else %}
+
+.intel_syntax noprefix
+.text
+.p2align 5
+.globl {{G}}avx512vnni_mmm_i32_8x8_{{suffix}}
+{{G}}avx512vnni_mmm_i32_8x8_{{suffix}}:
+.cfi_startproc
+
+{% endif %}
+
+    push        rbp
+    mov         rbp, rsp
+
+{% if family == "windows" %}
+// https://www.agner.org/optimize/calling_conventions.pdf xmm6-15 are not scratch
+// https://stackoverflow.com/questions/43358429/save-value-of-xmm-registers
+    and rsp,-16
+    lea rsp,[rsp-160]
+    vmovaps [rsp], xmm6
+    vmovaps [rsp+16*1],xmm7
+    vmovaps [rsp+16*2],xmm8
+    vmovaps [rsp+16*3],xmm9
+    vmovaps [rsp+16*4],xmm10
+    vmovaps [rsp+16*5],xmm11
+    vmovaps [rsp+16*6],xmm12
+    vmovaps [rsp+16*7],xmm13
+    vmovaps [rsp+16*8],xmm14
+    vmovaps [rsp+16*9],xmm15
+
+    push        rdi
+    push        rsi
+
+    mov         rdi, rcx
+
+{% endif %}
+
+    push        rbx
+    push        r12
+    push        r13
+    push        r14
+    push        r15
+
+    sub         rsp, 8
+
+{% if family == "unix" %}
+.cfi_def_cfa_offset 64
+{% endif %}
+
+    stmxcsr     [rsp + 4]
+{% if msvc %}
+    mov         rax, 1FC0h
+{% else %}
+    mov         rax, 0x1FC0
+{% endif %}
+    mov         [rsp], eax
+    ldmxcsr     [rsp]
+
+{% include "dispatcher.j2" %}
+
+{{L}}clear:
+    vzeroall
+    jmp     {{L}}non_linear_loop
+
+{{L}}add_mat_mul:
+    mov     r12,    [rdi + 32]   // packing
+    mov     rbx,    [rdi + 24]   // B
+    mov     rax,    [rdi + 16]   // A
+
+    mov     rcx,    [rdi + 8]    // k
+    test    rcx,    rcx
+    jz      {{L}}non_linear_loop
+
+    cmp     r12, 1
+    je      {{L}}main_loop_packed_packed_i8i8
+
+{{L}}main_loop_packed_packed:
+    vmovaps         ymm12,  [rax]
+
+    {% for i in range(0, 8) %}
+        vbroadcastss    ymm14, dword ptr [rbx + {{i}} * 4]
+        vpmulld         ymm13, ymm12, ymm14
+        vpaddd          ymm{{i}}, ymm{{i}}, ymm13
+    {% endfor %}
+
+    add             rax,    32
+    add             rbx,    32
+    dec             rcx
+    jnz             {{L}}main_loop_packed_packed
+
+    jmp             {{L}}non_linear_loop
+
+{{L}}main_loop_packed_packed_i8i8:
+    // PackedI8K4 layout: per K=4 block, the A panel is 8 rows x 4 K-bytes (32
+    // bytes, lane m = A[m, 4kb..4kb+3]) and the B panel is 8 cols x 4 K-bytes
+    // (lane n = B[n, 4kb..4kb+3]). VPDPBUSD is u8 x s8, so A is offset by +128
+    // (-> u8) and the resulting 128*sum_k(B[n]) bias is removed per column after
+    // the loop, leaving the i32 accumulators identical to the AVX2 path.
+
+    add             rcx,    3
+    shr             rcx,    2                      // rcx <- ceil(k/4) K=4 blocks
+
+    mov             r8d,    0x01010101
+    movd            xmm11,  r8d
+    vpbroadcastd    ymm11,  xmm11                  // ymm11 <- u8 ones (sum of B)
+
+    mov             r8d,    0x80808080
+    movd            xmm12,  r8d
+    vpbroadcastd    ymm12,  xmm12                  // ymm12 <- byte 0x80 (A + 128)
+
+    vpxor           ymm10,  ymm10,  ymm10          // ymm10 <- per-col sum_k B[n]
+
+{{L}}loop_4k_i8i8:
+    vmovdqu         ymm8,   [rax]                  // A block: lane m = A[m,4kb..]
+    vpaddb          ymm8,   ymm8,   ymm12          // s8 -> u8 (+128, modular)
+
+    vmovdqu         ymm9,   [rbx]                  // B block: lane n = B[n,4kb..]
+    vpdpbusd        ymm10,  ymm11,  ymm9           // sum_k B[n] += sum_t B[n,4kb+t]
+
+    {% for n in range(0, 8) %}
+    vpbroadcastd    ymm13,  dword ptr [rbx + {{n}} * 4]
+    vpdpbusd        ymm{{n}}, ymm8, ymm13          // acc[n][m] += sum_t (A[m]+128)*B[n]
+    {% endfor %}
+
+    add             rax,    32
+    add             rbx,    32
+    dec             rcx
+    jnz             {{L}}loop_4k_i8i8
+
+    // remove the +128 bias added on A: acc[n] -= 128 * sum_k B[n]
+    vpslld          ymm10,  ymm10,  7              // lane n <- 128 * sum_k B[n]
+    {% for n in range(0, 8) %}
+    mov             r8d,    {{n}}
+    movd            xmm14,  r8d
+    vpbroadcastd    ymm14,  xmm14                  // index = n in every lane
+    vpermd          ymm15,  ymm14,  ymm10          // splat 128*sum_k B[n]
+    vpsubd          ymm{{n}}, ymm{{n}}, ymm15
+    {% endfor %}
+
+    jmp             {{L}}non_linear_loop
+
+{% set from = 0 %}{% set to = 7 %}{% include "fma_mmm_i32_scalars.j2" %}
+{% set mr = 8 %}{% set from = 0 %}{% set to = 7 %}{% include "fma_mmm_i32_per_rows.j2" %}
+{% set mr = 8 %}{% set from = 0 %}{% set to = 7 %}{% include "fma_mmm_i32_per_cols.j2" %}
+{% set from = 0 %}{% set to = 7 %}{% include "fma_mmm_load_tile.j2" %}
+
+{{L}}add_unicast:
+
+    mov     r10,    [rdi + 8]           // c ptr
+    mov     rsi,    [rdi + 16]          // row stride
+    mov     rbx,    [rdi + 24]          // col stride
+    mov     r8,     [rdi + 32]          // item size
+
+    cmp     r8,    4
+    je      {{L}}non_linear_addc_i32
+
+{#
+// This is not great as vgatherdps reads 32-bits values and goes beyond our buffer. Probably harmless though.
+// Commented and replaced with the "mov al" loop beyond to pacify valgrind.
+// ymm14 and ymm15 are the same as in the non_linear_addc_i32 case (compute them before the test right above here.
+// {% for i in range(0, 8) %}
+//     vpcmpeqd        ymm15, ymm15, ymm15
+//     vgatherdps      ymm12, [ r10 + ymm14 ], ymm15   // 0xxx 1xxx 2xxx 3xxx 4xxx 5xxx 6xxx 7xxx
+//
+//     // we need to go through vpmovsxbd, shuffling naively erases signs
+//     vpshufb         ymm12, ymm12, ymm10             // 0123 0123 0123 0123 4567 4567 4567 4567
+//
+//     vpermd          ymm12, ymm11, ymm12             // 0123 4567
+//     vpmovsxbd       ymm12, xmm12                    // sign extend
+//
+//     vpaddd          ymm{{i}},   ymm{{i}},   ymm12
+//     add             r10, rbx
+// {% endfor %}
+#}
+
+    {% for col in range(0, 8) %}
+        mov r8, r10
+        {% for half in range(0, 2) %}
+            {% for lane in range(0, 4) %}
+                mov al, [ r8 ]
+                add r8, rsi
+                movsx eax, al
+                pinsrd xmm10, eax, {{lane}}
+            {% endfor %}
+            vperm2f128  ymm10,   ymm10,   ymm10,  1
+        {% endfor %}
+        vpaddd ymm{{col}}, ymm{{col}}, ymm10
+        add r10, rbx
+    {% endfor %}
+
+    jmp    {{L}}non_linear_loop
+
+{{L}}non_linear_addc_i32:
+
+    mov     eax,    0
+{% for i in range(0, 4) %}
+    pinsrd  xmm14, eax, {{i}}
+    add     eax,    esi
+{% endfor %}
+    vpermq          ymm14, ymm14, 78 // 0b01001110
+{% for i in range(0, 4) %}
+    pinsrd  xmm14, eax, {{i}}
+    add     eax,    esi
+{% endfor %}
+    vpermq          ymm14, ymm14, 78 // 0b01001110
+
+
+{% if msvc %}
+    vpbroadcastd    ymm10, dword ptr [ offset byte_shuffle ]
+    vmovups         ymm11, dword ptr [ offset i128_shuffle ]
+{% else %}
+    vpbroadcastd    ymm10, [ rip + {{L}}byte_shuffle ]
+    vmovups         ymm11, [ rip + {{L}}i128_shuffle ]
+{% endif %}
+
+{% for i in range(0, 8) %}
+    vpcmpeqd        ymm15, ymm15, ymm15
+    vgatherdps      ymm12, [ r10 + ymm14 ], ymm15
+    vpaddd          ymm{{i}},   ymm{{i}},   ymm12
+    add             r10, rbx
+{% endfor %}
+
+    jmp    {{L}}non_linear_loop
+
+{% if msvc %}
+.data
+byte_shuffle dd              201851904 // 0x0c080400
+i128_shuffle dd              0, 4
+.code
+{% else %}
+{{L}}byte_shuffle: .int            201851904 // 0x0c080400
+{{L}}i128_shuffle: .int            0, 4
+{% endif %}
+
+{{L}}add_row_col_products:
+    mov             rax, [ rdi + 8 ]
+    mov             rbx, [ rdi + 16 ]
+
+    vmovups         ymm12,  [rax]
+
+{% for i in range(0, 8) %}
+    vbroadcastss    ymm14, dword ptr [rbx + {{ i * 4 }} ]
+    vpmulld         ymm15, ymm12, ymm14
+    vpaddd          ymm{{i}}, ymm{{i}}, ymm15
+{% endfor %}
+    jmp    {{L}}non_linear_loop
+
+{{L}}q_scale:
+    mov             r8, [ rdi + 16 ]        // policy
+    vbroadcastss    ymm8, dword ptr [rdi + 24] // multi
+
+    mov             rax, 1
+    movq            xmm9, rax
+    vpbroadcastq    ymm9, xmm9              // ymm9 <- 1
+
+    mov             rax, [ rdi + 8 ]        // xmm10 <- shift + 31
+    add             rax, 31
+    movq            xmm10, rax
+    vpbroadcastq    ymm10, xmm10
+
+    mov             rax, 1
+    movq            xmm11, rax
+    vpsubq          ymm12, ymm10, ymm9      // shift+31 - 1
+    vpsllq          ymm11, ymm9, xmm12      // ymm11 <- 1 << (shift + 31 - 1)
+
+    cmp     r8, 1
+    je      {{L}}q_scale_rounding_zero
+    cmp     r8, 2
+    je      {{L}}q_scale_rounding_away
+    cmp     r8, 3
+    je      {{L}}q_scale_rounding_minus_inf
+    cmp     r8, 4
+    je      {{L}}q_scale_rounding_plus_inf
+    cmp     r8, 5
+    je      {{L}}q_scale_rounding_even
+    cmp     r8, 6
+    je      {{L}}q_scale_rounding_odd
+
+    jmp    {{L}}unsupported
+
+{{L}}q_scale_rounding_zero:           // signum * ( (abs + nudge) >> shift )
+{% for i in range(0, 8) %}
+    vpabsd      ymm14, ymm{{i}}
+    vpsrldq     ymm15, ymm14, 4             // ymm15 <- a1, a2, a3, a4, a5, a6, a7, 0
+    vpmuldq     ymm14, ymm14, ymm8          // ymm14  <- a0*c, a2*c, a4*c, a6*c
+    vpmuldq     ymm15, ymm15, ymm8          // ymm15 <- a1*c, a3*c, a5*c, a7*c
+
+    vpaddq      ymm14, ymm14, ymm11
+    vpaddq      ymm15, ymm15, ymm11
+
+    vpsubq      ymm14, ymm14, ymm9
+    vpsubq      ymm15, ymm15, ymm9
+
+    vpsrlq      ymm14, ymm14, xmm10
+    vpsrlq      ymm15, ymm15, xmm10
+
+    vpslldq     ymm15, ymm15, 4
+    vpblendd    ymm14, ymm15, ymm14, 85     // 0x55
+    vpsignd     ymm{{i}}, ymm14, ymm{{i}}
+{% endfor %}
+
+    jmp    {{L}}non_linear_loop
+
+{{L}}q_scale_rounding_away:           // signum * ( (abs + nudge) >> shift )
+{% for i in range(0, 8) %}
+    vpabsd      ymm14, ymm{{i}}
+    vpsrldq     ymm15, ymm14, 4             // ymm15 <- a1, a2, a3, a4, a5, a6, a7, 0
+    vpmuldq     ymm14, ymm14, ymm8          // ymm14  <- a0*c, a2*c, a4*c, a6*c
+    vpmuldq     ymm15, ymm15, ymm8          // ymm15 <- a1*c, a3*c, a5*c, a7*c
+
+    vpaddq      ymm14, ymm14, ymm11
+    vpaddq      ymm15, ymm15, ymm11
+
+    vpsrlq      ymm14, ymm14, xmm10
+    vpsrlq      ymm15, ymm15, xmm10
+
+    vpslldq     ymm15, ymm15, 4
+    vpblendd    ymm14, ymm15, ymm14, 85     // 0x55
+    vpsignd     ymm{{i}}, ymm14, ymm{{i}}
+{% endfor %}
+
+    jmp    {{L}}non_linear_loop
+
+{{L}}q_scale_rounding_minus_inf:           // signum * ( (abs << 32 + 1<<30+shift) >> shift )
+{% for i in range(0, 8) %}
+    vpabsd      ymm14, ymm{{i}}
+    // sign extract for nudging in the right direction
+    vpxor       ymm13, ymm13, ymm13
+    vpcmpgtd    ymm13, ymm{{i}}, ymm13      // ymm13 <- s0, s1, ..s8 (signums, as all ones or all zeros)
+    vpsrld      ymm13, ymm13, 31            // then just 0 or 1
+
+    vpsrldq     ymm15, ymm14, 4             // ymm15 <- a1, a2, a3, a4, a5, a6, a7, 0
+    vpmuldq     ymm14, ymm14, ymm8          // ymm14  <- a0*c, a2*c, a4*c, a6*c
+    vpmuldq     ymm15, ymm15, ymm8          // ymm15 <- a1*c, a3*c, a5*c, a7*c
+
+    vpaddq      ymm14, ymm14, ymm11
+    vpaddq      ymm15, ymm15, ymm11
+
+    // reinterpret ymm13=s0i32..s7 as i64 and blend with zero to pick the even ones as i64
+    vpxor       ymm12, ymm12, ymm12
+    vpblendd    ymm12, ymm12, ymm13, 85     // 0x55
+    vpsubq      ymm14, ymm14, ymm12
+
+    vpsrldq     ymm13, ymm13, 4             // ymm13 <- s1, s2, .., s7, 0
+    vpxor       ymm12, ymm12, ymm12
+    vpblendd    ymm12, ymm12, ymm13, 85     // 0x55
+    vpsubq      ymm15, ymm15, ymm12
+
+    vpsrlq      ymm14, ymm14, xmm10
+    vpsrlq      ymm15, ymm15, xmm10
+
+    vpslldq     ymm15, ymm15, 4
+    vpblendd    ymm14, ymm15, ymm14, 85     // 0x55
+    vpsignd     ymm{{i}}, ymm14, ymm{{i}}
+{% endfor %}
+
+    jmp    {{L}}non_linear_loop
+
+{{L}}q_scale_rounding_plus_inf:           // signum * ( (abs << 32 + 1<<30+shift) >> shift )
+
+    vpbroadcastd ymm9, xmm9
+
+{% for i in range(0, 8) %}
+    vpabsd      ymm14, ymm{{i}}
+    vpxor       ymm13, ymm13, ymm13
+
+    // sign extract for nudging in the right direction
+    vpcmpgtd    ymm13, ymm{{i}}, ymm13      // ymm13 <- s0, s1, ..s8 (signums, as all ones or all zeros)
+    vpaddd      ymm13, ymm13, ymm9          // if val >= 0 { 0i32 } else { 1i32 }
+
+    vpsrldq     ymm15, ymm14, 4             // ymm15 <- a1, a2, a3, a4, a5, a6, a7, 0
+    vpmuldq     ymm14, ymm14, ymm8          // ymm14  <- a0*c, a2*c, a4*c, a6*c
+    vpmuldq     ymm15, ymm15, ymm8          // ymm15 <- a1*c, a3*c, a5*c, a7*c
+
+    vpaddq      ymm14, ymm14, ymm11
+    vpaddq      ymm15, ymm15, ymm11
+
+    // reinterpret ymm13=s0i32..s7 as i64 and blend with zero to pick the even ones as i64
+    vpxor       ymm12, ymm12, ymm12
+    vpblendd    ymm12, ymm12, ymm13, 85     // 0x55
+    vpsubq      ymm14, ymm14, ymm12
+
+    vpsrldq     ymm13, ymm13, 4             // ymm13 <- s1, s2, .., s7, 0
+    vpxor       ymm12, ymm12, ymm12
+    vpblendd    ymm12, ymm12, ymm13, 85     // 0x55
+    vpsubq      ymm15, ymm15, ymm12
+
+    vpsrlq      ymm14, ymm14, xmm10
+    vpsrlq      ymm15, ymm15, xmm10
+
+    vpslldq     ymm15, ymm15, 4
+    vpblendd    ymm14, ymm15, ymm14, 85     // 0x55
+    vpsignd     ymm{{i}}, ymm14, ymm{{i}}
+{% endfor %}
+
+    jmp    {{L}}non_linear_loop
+
+{{L}}q_scale_rounding_even:           // signum * ( (abs + nudge) >> shift )
+{% for i in range(0, 8) %}
+    vpabsd      ymm14, ymm{{i}}
+    vpsrldq     ymm15, ymm14, 4             // ymm15 <- a1, a2, a3, a4, a5, a6, a7, 0
+    vpmuldq     ymm14, ymm14, ymm8          // ymm14  <- a0*c, a2*c, a4*c, a6*c
+    vpmuldq     ymm15, ymm15, ymm8          // ymm15 <- a1*c, a3*c, a5*c, a7*c
+
+    vpsrlq      ymm12, ymm14, xmm10
+    vpand       ymm12, ymm12, ymm9
+    vpaddq      ymm14, ymm14, ymm12
+    vpsubq      ymm14, ymm14, ymm9
+
+    vpsrlq      ymm12, ymm15, xmm10
+    vpand       ymm12, ymm12, ymm9
+    vpaddq      ymm15, ymm15, ymm12
+    vpsubq      ymm15, ymm15, ymm9
+
+    vpaddq      ymm14, ymm14, ymm11
+    vpaddq      ymm15, ymm15, ymm11
+
+    vpsrlq      ymm14, ymm14, xmm10
+    vpsrlq      ymm15, ymm15, xmm10
+
+    vpslldq     ymm15, ymm15, 4
+    vpblendd    ymm14, ymm15, ymm14, 85     // 0x55
+    vpsignd     ymm{{i}}, ymm14, ymm{{i}}
+{% endfor %}
+    jmp    {{L}}non_linear_loop
+
+{{L}}q_scale_rounding_odd:           // signum * ( (abs + nudge) >> shift )
+{% for i in range(0, 8) %}
+    vpabsd      ymm14, ymm{{i}}
+    vpsrldq     ymm15, ymm14, 4             // ymm15 <- a1, a2, a3, a4, a5, a6, a7, 0
+    vpmuldq     ymm14, ymm14, ymm8          // ymm14  <- a0*c, a2*c, a4*c, a6*c
+    vpmuldq     ymm15, ymm15, ymm8          // ymm15 <- a1*c, a3*c, a5*c, a7*c
+
+    vpsrlq      ymm12, ymm14, xmm10
+    vpand       ymm12, ymm12, ymm9
+    vpsubq      ymm14, ymm14, ymm12
+
+    vpsrlq      ymm12, ymm15, xmm10
+    vpand       ymm12, ymm12, ymm9
+    vpsubq      ymm15, ymm15, ymm12
+
+    vpaddq      ymm14, ymm14, ymm11
+    vpaddq      ymm15, ymm15, ymm11
+
+    vpsrlq      ymm14, ymm14, xmm10
+    vpsrlq      ymm15, ymm15, xmm10
+
+    vpslldq     ymm15, ymm15, 4
+    vpblendd    ymm14, ymm15, ymm14, 85     // 0x55
+    vpsignd     ymm{{i}}, ymm14, ymm{{i}}
+{% endfor %}
+
+    jmp    {{L}}non_linear_loop
+
+{{L}}q_shl:
+    mov             eax, [ rdi + 8 ]        // xmm10 <- -shift (8 times)
+    movd            xmm10, eax
+    vpbroadcastd    ymm10, xmm10
+
+{% for i in range(0, 8) %}
+    vpsllvd     ymm{{i}}, ymm{{i}}, ymm10
+{% endfor %}
+    jmp     {{L}}non_linear_loop
+
+{{L}}q_shr:
+    mov             r8, [ rdi + 16 ]        // policy
+
+    mov             eax, 1
+    movd            xmm9, eax
+    vpbroadcastd    ymm9, xmm9              // ymm9 <- 1u32 (8 times)
+
+    mov             eax, [ rdi + 8 ]        // xmm10 <- shift (8 times)
+    movd            xmm10, eax
+    vpbroadcastd    ymm10, xmm10
+
+    mov             ebx, 1
+    mov             cl, al
+    sub             cl, 1                  // rcx <- shift -1
+    sal             ebx, cl                // rbx <- (1 << (shift - 1))
+    movd            xmm11, ebx
+    vpbroadcastd    ymm11, xmm11            // ymm11 <- "half"
+
+    vpxor           ymm12, ymm12, ymm12     // ymm12 <- zeroes
+
+    cmp     r8, 1
+    je      {{L}}q_shr_rounding_zero
+    cmp     r8, 2
+    je      {{L}}q_shr_rounding_away
+    cmp     r8, 3
+    je      {{L}}q_shr_rounding_minus_inf
+    cmp     r8, 4
+    je      {{L}}q_shr_rounding_plus_inf
+    cmp     r8, 5
+    je      {{L}}q_shr_rounding_even
+    cmp     r8, 6
+    je      {{L}}q_shr_rounding_odd
+
+    jmp    {{L}}unsupported
+
+{{L}}q_shr_rounding_zero:
+{% for i in range(0, 8) %}
+    vpabsd      ymm14, ymm{{i}}
+    vpsubd      ymm14, ymm14, ymm9
+    vpaddd      ymm14, ymm14, ymm11
+    vpsravd     ymm14, ymm14, ymm10
+    vpsignd     ymm{{i}}, ymm14, ymm{{i}}
+{% endfor %}
+    jmp     {{L}}non_linear_loop
+
+{{L}}q_shr_rounding_away:
+{% for i in range(0, 8) %}
+    vpabsd      ymm14, ymm{{i}}
+    vpaddd      ymm14, ymm14, ymm11
+    vpsravd     ymm14, ymm14, ymm10
+    vpsignd     ymm{{i}}, ymm14, ymm{{i}}
+{% endfor %}
+    jmp     {{L}}non_linear_loop
+
+{{L}}q_shr_rounding_minus_inf:
+{% for i in range(0, 8) %}
+    vpsubd  ymm{{i}}, ymm{{i}}, ymm9
+    vpaddd  ymm{{i}}, ymm{{i}}, ymm11
+    vpsravd ymm{{i}}, ymm{{i}}, ymm10
+{% endfor %}
+    jmp     {{L}}non_linear_loop
+
+{{L}}q_shr_rounding_plus_inf:
+{% for i in range(0, 8) %}
+    vpaddd  ymm{{i}}, ymm{{i}}, ymm11
+    vpsravd ymm{{i}}, ymm{{i}}, ymm10
+{% endfor %}
+    jmp     {{L}}non_linear_loop
+
+{{L}}q_shr_rounding_even:
+{% for i in range(0, 8) %}
+    vpabsd      ymm14, ymm{{i}}
+    vpsravd ymm13, ymm14, ymm10
+    vpand   ymm13, ymm13, ymm9
+    vpsubd  ymm13, ymm13, ymm9          // nudge = ((abs >>l shift) & 0x01) - 1
+    vpaddd  ymm14, ymm14, ymm13         // add nudge
+    vpaddd  ymm14, ymm14, ymm11         // add half
+    vpsravd ymm14, ymm14, ymm10
+    vpsignd     ymm{{i}}, ymm14, ymm{{i}}
+{% endfor %}
+    jmp     {{L}}non_linear_loop
+
+{{L}}q_shr_rounding_odd:
+{% for i in range(0, 8) %}
+    vpabsd      ymm14, ymm{{i}}
+    vpsravd ymm13, ymm14, ymm10
+    vpand   ymm13, ymm13, ymm9
+    vpsubd  ymm13, ymm12, ymm13          // nudge = - ((abs >>l shift) & 0x01)
+    vpaddd  ymm14, ymm14, ymm13         // add nudge
+    vpaddd  ymm14, ymm14, ymm11         // add half
+    vpsravd ymm14, ymm14, ymm10
+    vpsignd     ymm{{i}}, ymm14, ymm{{i}}
+{% endfor %}
+    jmp     {{L}}non_linear_loop
+
+{{L}}store:
+    mov     r8,     [rdi + 8]           // c ptr
+    mov     rsi,    [rdi + 16]          // row stride
+    mov     rdx,    [rdi + 24]          // col stride
+    mov     rcx,    [rdi + 32]          // item size
+
+    cmp     rcx,    4
+    je      {{L}}store_strides_i32
+
+    {% for col in range(0, 8) %}
+        mov r10, r8
+        {% for row in range(0, 4) %}
+            extractps   ebx, xmm{{col}}, {{row}}
+            mov         byte ptr [r10], bl
+            add         r10, rsi
+        {% endfor %}
+        vperm2f128  ymm{{col}},   ymm{{col}},   ymm{{col}},  1
+        {% for row in range(0, 4) %}
+            extractps   ebx, xmm{{col}}, {{row}}
+            mov         byte ptr [r10], bl
+            add         r10, rsi
+        {% endfor %}
+        add r8, rdx
+    {% endfor %}
+
+    jmp     {{L}}non_linear_loop
+
+{{L}}store_strides_i32:
+    {% for col in range(0, 8) %}
+        mov r10,    r8
+        {% for row in range(0, 4) %}
+            extractps   ebx, xmm{{col}}, {{row}}
+            mov         dword ptr [r10], ebx
+            add         r10, rsi
+        {% endfor %}
+        vperm2f128  ymm{{col}},   ymm{{col}},   ymm{{col}},  1
+        {% for row in range(0, 4) %}
+            extractps   ebx, xmm{{col}}, {{row}}
+            mov         dword ptr [r10], ebx
+            add         r10, rsi
+        {% endfor %}
+        add r8, rdx
+    {% endfor %}
+
+    jmp     {{L}}non_linear_loop
+
+{{L}}return:
+    ldmxcsr     [rsp + 4]
+    add         rsp, 8
+
+    pop r15
+    pop r14
+    pop r13
+    pop r12
+    pop rbx
+
+{% if family == "windows" %}
+    pop rsi
+    pop rdi
+
+    vmovaps xmm15, [rsp+16*9]
+    vmovaps xmm14, [rsp+16*8]
+    vmovaps xmm13, [rsp+16*7]
+    vmovaps xmm12, [rsp+16*6]
+    vmovaps xmm11, [rsp+16*5]
+    vmovaps xmm10, [rsp+16*4]
+    vmovaps xmm9, [rsp+16*3]
+    vmovaps xmm8, [rsp+16*2]
+    vmovaps xmm7, [rsp+16*1]
+    vmovaps xmm6, [rsp]
+{% endif %}
+
+    mov rsp, rbp
+    pop rbp
+    ret
+
+
+{{L}}one_32bit:
+{% if msvc %}
+    dd      1
+{% else %}
+    .int    1
+{% endif %}
+
+{% if msvc %}
+avx512vnni_mmm_i32_8x8_{{suffix}} endp
+_text ends
+end
+{% else %}
+.cfi_endproc
+{% endif %}
diff --git a/metal/Cargo.toml b/metal/Cargo.toml
index 17ffd1b341..43103d21b2 100644
--- a/metal/Cargo.toml
+++ b/metal/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-metal"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 license = "MIT OR Apache-2.0"
 authors = [
 	"Hubert de La Jonquière <hubert.delajonquiere@sonos.com>",
diff --git a/nnef/Cargo.toml b/nnef/Cargo.toml
index 2051d393b5..982057aa38 100644
--- a/nnef/Cargo.toml
+++ b/nnef/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-nnef"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 authors = ["Mathieu Poumeyrol <kali@zoy.org>"]
 license = "MIT OR Apache-2.0"
 description = "Tiny, no-nonsense, self contained, TensorFlow and ONNX inference"
diff --git a/nnef/nnef-resources/Cargo.toml b/nnef/nnef-resources/Cargo.toml
index 03a6838d85..8220ba44e0 100644
--- a/nnef/nnef-resources/Cargo.toml
+++ b/nnef/nnef-resources/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-nnef-resources"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 authors = [
 	"Mathieu Poumeyrol <kali@zoy.org>",
 	"Hubert de La Jonquière <hubert.delajonquiere@sonos.com>"
diff --git a/nnef/src/transform.rs b/nnef/src/transform.rs
index 414f0a2a5a..186b0d3530 100644
--- a/nnef/src/transform.rs
+++ b/nnef/src/transform.rs
@@ -87,7 +87,6 @@ impl ModelTransform for PatchTransform {
         // Build the TypedModelPatch
         let mut patch = TypedModelPatch { model: patch_model, taps, ..TypedModelPatch::default() };
 
-        let mut inputs_to_remove = vec![];
         let mut new_output_names = vec![];
 
         for (i, lhs_name) in lhs_names.iter().enumerate() {
@@ -124,15 +123,19 @@ impl ModelTransform for PatchTransform {
                         &[wire],
                     )?[0];
                 }
+                // Shunt consumers of the input outlet to the new wire.  Like
+                // `TypedModelPatch::shunt_outside` we do NOT touch
+                // `model.inputs` — the original input stays in the list as
+                // a disconnected Source.  Use `select_inputs(...)` after the
+                // patch to drop it explicitly.
                 patch.shunt_outside(model, input_outlet, wire)?;
-                inputs_to_remove.push(input_outlet);
             } else if self.0.new_outputs.contains(lhs_name) {
                 new_output_names.push(lhs_name.clone());
             } else {
                 let is_intermediate = i < lhs_names.len() - 1;
                 if !is_intermediate {
                     bail!(
-                        "Wire '{}' is not a model input and not declared in new_outputs",
+                        "Wire '{}' is not a model input/intermediate and not declared in new_outputs",
                         lhs_name
                     );
                 }
@@ -141,9 +144,6 @@ impl ModelTransform for PatchTransform {
 
         patch.apply(model)?;
 
-        for inp in &inputs_to_remove {
-            model.inputs.retain(|o| o != inp);
-        }
         for name in &new_output_names {
             let node_id = model.node_id_by_name(name)?;
             model.outputs.push(OutletId::new(node_id, 0));
diff --git a/onnx-opl/Cargo.toml b/onnx-opl/Cargo.toml
index ca43b47230..de71ad7f0e 100644
--- a/onnx-opl/Cargo.toml
+++ b/onnx-opl/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-onnx-opl"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 authors = ["Mathieu Poumeyrol <kali@zoy.org>"]
 license = "MIT OR Apache-2.0"
 description = "Tiny, no-nonsense, self contained, TensorFlow and ONNX inference"
diff --git a/onnx/Cargo.toml b/onnx/Cargo.toml
index 8623cf64bd..7e36dbec44 100644
--- a/onnx/Cargo.toml
+++ b/onnx/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-onnx"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 authors = ["Mathieu Poumeyrol <kali@zoy.org>"]
 license = "MIT OR Apache-2.0"
 description = "Tiny, no-nonsense, self contained, TensorFlow and ONNX inference"
diff --git a/onnx/src/ops/nn/group_query_attention.rs b/onnx/src/ops/nn/group_query_attention.rs
new file mode 100644
index 0000000000..4de7657d1c
--- /dev/null
+++ b/onnx/src/ops/nn/group_query_attention.rs
@@ -0,0 +1,169 @@
+use crate::model::ParsingContext;
+use crate::pb::NodeProto;
+use tract_core::ops::change_axes::AxisOp;
+use tract_hir::internal::*;
+use tract_transformers::ops::sdpa::Sdpa;
+
+// com.microsoft GroupQueryAttention (prefill only).
+//   inputs:  query(0), key(1), value(2), past_key(3), past_value(4), seqlens_k(5), total_seq(6)
+//   outputs: output(0), present_key(1), present_value(2)
+// Scoped to the prefill case (no past KV cache): query/key/value are [B, S, heads*head_size],
+// attention is causal with q_seq == kv_seq, and present_key/value are the reshaped K/V.
+// Decode-step KV cache, internal rotary (do_rotary) and local-window attention are rejected.
+pub fn group_query_attention(
+    _ctx: &ParsingContext,
+    node: &NodeProto,
+) -> TractResult<(Box<dyn InferenceOp>, Vec<String>)> {
+    let num_heads: usize = node.get_attr("num_heads")?;
+    let kv_num_heads: usize = node.get_attr("kv_num_heads")?;
+    let scale = node.get_attr_opt::<f32>("scale")?;
+    ensure!(
+        node.get_attr_opt::<i64>("do_rotary")?.unwrap_or(0) == 0,
+        "GroupQueryAttention: internal rotary (do_rotary) is unsupported; apply RotaryEmbedding separately"
+    );
+    ensure!(
+        node.get_attr_opt::<i64>("local_window_size")?.unwrap_or(-1) < 0,
+        "GroupQueryAttention: local_window_size is unsupported"
+    );
+    ensure!(
+        node.get_attr_opt::<f32>("softcap")?.unwrap_or(0.0) == 0.0,
+        "GroupQueryAttention: softcap is unsupported"
+    );
+    let have_past = (node.input.len() > 3 && !node.input[3].is_empty())
+        || (node.input.len() > 4 && !node.input[4].is_empty());
+    ensure!(
+        !have_past,
+        "GroupQueryAttention: past KV cache (decode step) is unsupported; only prefill is handled"
+    );
+    Ok((expand(GroupQueryAttention { num_heads, kv_num_heads, scale }), vec![]))
+}
+
+#[derive(Debug, Clone)]
+struct GroupQueryAttention {
+    num_heads: usize,
+    kv_num_heads: usize,
+    scale: Option<f32>,
+}
+
+// [B, S, heads*head_size] -> [B, heads, S, head_size]
+fn to_4d(
+    model: &mut TypedModel,
+    prefix: &str,
+    x: OutletId,
+    total: TDim,
+    heads: usize,
+) -> TractResult<OutletId> {
+    let head_dim = total.clone() / heads;
+    let reshaped = model.wire_node(
+        format!("{prefix}.reshape"),
+        AxisOp::Reshape(2, tvec![total], tvec![heads.to_dim(), head_dim]),
+        &[x],
+    )?[0];
+    Ok(model.wire_node(format!("{prefix}.transpose"), AxisOp::Move(2, 1), &[reshaped])?[0])
+}
+
+impl Expansion for GroupQueryAttention {
+    fn name(&self) -> StaticName {
+        "GroupQueryAttention".into()
+    }
+
+    fn nboutputs(&self) -> TractResult<usize> {
+        Ok(3)
+    }
+
+    fn rules<'r, 'p: 'r, 's: 'r>(
+        &'s self,
+        s: &mut Solver<'r>,
+        inputs: &'p [TensorProxy],
+        outputs: &'p [TensorProxy],
+    ) -> InferenceResult {
+        check_output_arity(outputs, 3)?;
+        s.equals(&inputs[0].datum_type, &outputs[0].datum_type)?;
+        s.equals(&inputs[0].shape, &outputs[0].shape)?;
+        s.equals(&inputs[0].datum_type, &outputs[1].datum_type)?;
+        s.equals(&inputs[0].datum_type, &outputs[2].datum_type)?;
+        // present_key / present_value = key/value reshaped to [B, kv_num_heads, S, head_dim].
+        let kvh = self.kv_num_heads;
+        s.given(&inputs[1].shape, move |s, ks| {
+            s.equals(
+                &outputs[1].shape,
+                tvec![ks[0].clone(), kvh.to_dim(), ks[1].clone(), ks[2].clone() / kvh],
+            )
+        })?;
+        s.given(&inputs[2].shape, move |s, vs| {
+            s.equals(
+                &outputs[2].shape,
+                tvec![vs[0].clone(), kvh.to_dim(), vs[1].clone(), vs[2].clone() / kvh],
+            )
+        })?;
+        Ok(())
+    }
+
+    fn wire(
+        &self,
+        prefix: &str,
+        model: &mut TypedModel,
+        inputs: &[OutletId],
+    ) -> TractResult<TVec<OutletId>> {
+        let q_fact = model.outlet_fact(inputs[0])?.clone();
+        let dt = q_fact.datum_type;
+        ensure!(q_fact.rank() == 3, "GroupQueryAttention: expected 3D query [B, S, hidden]");
+        let q_hidden = q_fact.shape[2].clone();
+        let k_hidden = model.outlet_fact(inputs[1])?.shape[2].clone();
+        let v_hidden = model.outlet_fact(inputs[2])?.shape[2].clone();
+
+        let q4 = to_4d(model, &format!("{prefix}.q"), inputs[0], q_hidden.clone(), self.num_heads)?;
+        let k4 = to_4d(model, &format!("{prefix}.k"), inputs[1], k_hidden, self.kv_num_heads)?;
+        let v4 = to_4d(model, &format!("{prefix}.v"), inputs[2], v_hidden, self.kv_num_heads)?;
+
+        // Causal mask: materialise an explicit additive lower-triangular mask for concrete
+        // shapes (exact ONNX semantics: query i attends to keys j <= i); fall back to Sdpa's
+        // own is_causal for symbolic shapes. Sdpa handles GQA head grouping (kv heads < q heads).
+        let q_seq = model.outlet_fact(q4)?.shape[2].to_usize().ok();
+        let kv_seq = model.outlet_fact(k4)?.shape[2].to_usize().ok();
+        let (mask, is_causal) = if let (Some(qs), Some(ks)) = (q_seq, kv_seq) {
+            let arr = tract_ndarray::Array2::<f32>::from_shape_fn((qs, ks), |(i, j)| {
+                if j <= i { 0.0f32 } else { f32::NEG_INFINITY }
+            });
+            let mask_tensor: Tensor = arr.into();
+            let mut m = model.add_const(format!("{prefix}.causal_mask"), mask_tensor)?;
+            for i in 0..2 {
+                m = model.wire_node(
+                    format!("{prefix}.mask_unsqueeze_{i}"),
+                    AxisOp::Add(0),
+                    &[m],
+                )?[0];
+            }
+            (Some(m), false)
+        } else {
+            (None, true)
+        };
+        let mut sdpa_inputs = tvec![q4, k4, v4];
+        if let Some(m) = mask {
+            sdpa_inputs.push(m);
+        }
+        let sdpa = Sdpa {
+            scale: self.scale.map(tensor0),
+            datum_type: dt,
+            acc_datum_type: DatumType::F32,
+            is_causal,
+        };
+        let y4 = model.wire_node(format!("{prefix}.sdpa"), sdpa, &sdpa_inputs)?[0];
+
+        // [B, num_heads, S, head_dim] -> [B, S, num_heads, head_dim] -> [B, S, hidden]
+        let y_t = model.wire_node(format!("{prefix}.y_transpose"), AxisOp::Move(1, 2), &[y4])?[0];
+        let yf = model.outlet_fact(y4)?.clone();
+        let (heads_dim, head_dim) = (yf.shape[1].clone(), yf.shape[3].clone());
+        let y = model.wire_node(
+            format!("{prefix}.y_reshape"),
+            AxisOp::Reshape(
+                2,
+                tvec![heads_dim.clone(), head_dim.clone()],
+                tvec![heads_dim * head_dim],
+            ),
+            &[y_t],
+        )?[0];
+
+        Ok(tvec!(y, k4, v4))
+    }
+}
diff --git a/onnx/src/ops/nn/layer_norm.rs b/onnx/src/ops/nn/layer_norm.rs
index c84018e86c..c7daa62b56 100644
--- a/onnx/src/ops/nn/layer_norm.rs
+++ b/onnx/src/ops/nn/layer_norm.rs
@@ -161,20 +161,20 @@ impl Expansion for LayerNorm {
         let normalized =
             model.wire_node(format!("{prefix}.normalized"), mul(), &[d[0], inv_std_dev[0]])?;
         // NormalizedScaled = Mul(Normalized, Scale) Y = Add(NormalizedScaled, B)
-        let cast_normalized = model.wire_node(
-            format!("{prefix}.cast_normalized"),
-            cast(fact.datum_type),
-            &normalized,
-        )?;
+        // Keep `normalized` in self.datum_type (typically F32) through the
+        // scale/bias application, then cast back to fact.datum_type at the
+        // very end. Casting back too early causes a type mismatch with
+        // `cast_scale` / `cast_bias` (which are in self.datum_type), which
+        // breaks F16-input LayerNorm (output is F32 but fact says F16).
         let normalized_scaled = wire_with_rank_broadcast(
             format!("{prefix}.normalized_scaled"),
             model,
             mul(),
-            &[cast_normalized[0], cast_scale[0]],
+            &[normalized[0], cast_scale[0]],
         )?;
-        let y = if let Some(bias) = cast_bias {
+        let y_internal = if let Some(bias) = cast_bias {
             wire_with_rank_broadcast(
-                format!("{prefix}.y"),
+                format!("{prefix}.y_internal"),
                 model,
                 add(),
                 &[normalized_scaled[0], bias[0]],
@@ -182,6 +182,7 @@ impl Expansion for LayerNorm {
         } else {
             normalized_scaled
         };
+        let y = model.wire_node(format!("{prefix}.cast_y"), cast(fact.datum_type), &y_internal)?;
         let mut outputs = tvec!(y[0]);
         if self.mean_output.is_some() {
             outputs.push(reduced_mean_x[0]);
diff --git a/onnx/src/ops/nn/mod.rs b/onnx/src/ops/nn/mod.rs
index ad6056574b..c0434a6365 100644
--- a/onnx/src/ops/nn/mod.rs
+++ b/onnx/src/ops/nn/mod.rs
@@ -14,6 +14,7 @@ mod dropout;
 mod gelu;
 mod gelu_contrib;
 mod group_norm;
+mod group_query_attention;
 mod instance_norm;
 mod layer_norm;
 mod lp_norm;
@@ -93,6 +94,7 @@ pub fn register_all_ops(reg: &mut OnnxOpRegister) {
     reg.insert("BiasGelu", gelu_contrib::bias_gelu);
     reg.insert("FastGelu", gelu_contrib::fast_gelu);
     reg.insert("QuickGelu", gelu_contrib::quick_gelu);
+    reg.insert("GroupQueryAttention", group_query_attention::group_query_attention);
     reg.insert("HardSwish", |_, _| Ok((ops::nn::hard_swish().into_hir(), vec![])));
     reg.insert("Mish", |_, _| Ok((expand(mish::Mish), vec![])));
     reg.insert("MultiHeadAttention", multi_head_attention::multi_head_attention);
diff --git a/post-release.sh b/post-release.sh
index e6c49decad..dd1e48672f 100755
--- a/post-release.sh
+++ b/post-release.sh
@@ -12,7 +12,13 @@ fi
 
 if [ -z "$VERSION" ]
 then
-    echo "Usage: $0 <version>" 
+    echo "Usage: $0 <version>"
+    exit 1
+fi
+
+if ! echo "$VERSION" | grep -qE '^[0-9]+\.[0-9]+\.[0-9]+([.-][A-Za-z0-9.-]+)?$'
+then
+    echo "Refusing version '$VERSION': must look like 0.23.0 or 0.23.0-pre (no leading 'v')." >&2
     exit 1
 fi
 
diff --git a/pulse-opl/Cargo.toml b/pulse-opl/Cargo.toml
index 4ba12dfa53..fba02c9d2b 100644
--- a/pulse-opl/Cargo.toml
+++ b/pulse-opl/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-pulse-opl"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 license = "MIT OR Apache-2.0"
 authors = ["Mathieu Poumeyrol <kali@zoy.org>"]
 description = "Tiny, no-nonsense, self contained, TensorFlow and ONNX inference"
diff --git a/pulse/Cargo.toml b/pulse/Cargo.toml
index 698f4061f6..504cb1973e 100644
--- a/pulse/Cargo.toml
+++ b/pulse/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-pulse"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 license = "MIT OR Apache-2.0"
 authors = ["Mathieu Poumeyrol <kali@zoy.org>"]
 description = "Tiny, no-nonsense, self contained, TensorFlow and ONNX inference"
diff --git a/pulse/src/blockify.rs b/pulse/src/blockify.rs
index 10c4cf1f17..65f4c41e48 100644
--- a/pulse/src/blockify.rs
+++ b/pulse/src/blockify.rs
@@ -30,7 +30,7 @@
 //!    Determine the score axis the terminator contracts and translate
 //!    it to mask frame.
 //! 2. **Substitute** the streaming symbol globally `T → k·S` via core's
-//!    `substitute_symbols`.
+//!    `set_symbols`.
 //! 3. **Rewrite** one `TypedModelPatch` per section
 //!    (`build_section_patch`).  Sections are independent so patches
 //!    apply in sequence.  A recognised section gets fully rewritten or
@@ -188,7 +188,7 @@ impl ModelTransform for BlockifyTransform {
         let chunk_sym = model.symbols.new_with_prefix("S");
         let subs: HashMap<Symbol, TDim> =
             HashMap::from([(stream_sym.clone(), chunk_sym.to_dim() * k)]);
-        let new_model = model.substitute_symbols(&subs)?;
+        let new_model = model.set_symbols(&subs)?;
         *model = new_model;
         rewrite_sections(model, &chunk_sym, k)?;
         model.properties.insert(
diff --git a/pulse/src/model.rs b/pulse/src/model.rs
index d84ea20dd0..b825946c01 100644
--- a/pulse/src/model.rs
+++ b/pulse/src/model.rs
@@ -102,7 +102,7 @@ fn pulse_driven_blockify(
     model.symbols.add_assertion(format!("{chunk_sym} >= 0"))?;
     let subs: HashMap<Symbol, TDim> =
         HashMap::from([(symbol.clone(), chunk_sym.to_dim() * pulse_value)]);
-    *model = model.substitute_symbols(&subs)?;
+    *model = model.set_symbols(&subs)?;
     crate::blockify::rewrite_sections(model, &chunk_sym, pulse_value)?;
     model.properties.insert(
         crate::blockify::BLOCKIFY_ORIGINAL_SYMBOL.to_string(),
diff --git a/release.sh b/release.sh
index 5692a80405..c23ed77b7d 100755
--- a/release.sh
+++ b/release.sh
@@ -13,11 +13,17 @@ VERSION=$2
 
 if [ -z "$VERSION" ]
 then
-    echo "Usage: $0 <crate> <version>" 
+    echo "Usage: $0 <crate> <version>"
     echo crates order is: $ALL_CRATES_PATH
     exit 1
 fi
 
+if ! echo "$VERSION" | grep -qE '^[0-9]+\.[0-9]+\.[0-9]+([.-][A-Za-z0-9.-]+)?$'
+then
+    echo "Refusing version '$VERSION': must look like 0.23.0 or 0.23.0-pre (no leading 'v')." >&2
+    exit 1
+fi
+
 set -ex
 
 if [ "$CRATE_PATH" = "all" ]
diff --git a/tensorflow/Cargo.toml b/tensorflow/Cargo.toml
index b809644cd7..7783b0ce44 100644
--- a/tensorflow/Cargo.toml
+++ b/tensorflow/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-tensorflow"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 authors = ["Mathieu Poumeyrol <kali@zoy.org>"]
 license = "MIT OR Apache-2.0"
 description = "Tiny, no-nonsense, self contained, TensorFlow and ONNX inference"
@@ -22,7 +22,6 @@ log.workspace = true
 memmap2.workspace = true
 prost.workspace = true
 prost-types.workspace = true
-tensorflow = { workspace = true, optional = true }
 tract-hir.workspace = true
 tract-pulse.workspace = true
 
@@ -30,9 +29,6 @@ tract-pulse.workspace = true
 # protobuf-src = "1.0.5+3.19.3"
 # prost-build = "0.14"
 
-[features]
-conform = [ "tensorflow" ]
-
 [dev-dependencies]
 criterion.workspace = true
 env_logger.workspace = true
diff --git a/tensorflow/src/conform/mod.rs b/tensorflow/src/conform/mod.rs
deleted file mode 100644
index 8ec61a57d4..0000000000
--- a/tensorflow/src/conform/mod.rs
+++ /dev/null
@@ -1,48 +0,0 @@
-#![allow(unused)]
-#![allow(deprecated)]
-#![allow(non_snake_case)]
-
-pub mod tf;
-
-use crate::tfpb;
-use crate::tfpb::tensorflow::tensor_shape_proto::Dim;
-use crate::tfpb::tensorflow::{DataType, TensorProto, TensorShapeProto};
-use std::convert::TryInto;
-use tract_hir::internal::*;
-
-pub fn placeholder<Shape: Into<Option<TensorShapeProto>>>(
-    name: &str,
-    t: DataType,
-    shape: Shape,
-) -> tfpb::tensorflow::NodeDef {
-    let mut node = tfpb::node().name(name).op("Placeholder").attr("dtype", t);
-    if let Some(shape) = shape.into() {
-        node = node.attr("shape", shape)
-    }
-    node
-}
-
-pub fn tensor_shape(dims: &[usize]) -> TensorShapeProto {
-    TensorShapeProto {
-        dim: dims.iter().map(|&d| Dim { size: d as i64, name: String::new() }).collect(),
-        unknown_rank: false,
-    }
-}
-
-pub fn const_f32(name: &str, t: &Tensor) -> tfpb::tensorflow::NodeDef {
-    let tf: TensorProto = t.cast_to::<f32>().unwrap().as_ref().try_into().unwrap();
-    tfpb::node().name(name).op("Const").attr("dtype", DataType::DtFloat).attr("value", tf)
-}
-
-pub fn placeholder_f32(name: &str) -> tfpb::tensorflow::NodeDef {
-    placeholder(name, DataType::DtFloat, None)
-}
-
-pub fn const_i32(name: &str, t: &Tensor) -> tfpb::tensorflow::NodeDef {
-    let tf: TensorProto = t.cast_to::<i32>().unwrap().as_ref().try_into().unwrap();
-    tfpb::node().name(name).op("Const").attr("dtype", DataType::DtInt32).attr("value", tf)
-}
-
-pub fn placeholder_i32(name: &str) -> tfpb::tensorflow::NodeDef {
-    placeholder(name, DataType::DtInt32, None)
-}
diff --git a/tensorflow/src/conform/tf.rs b/tensorflow/src/conform/tf.rs
deleted file mode 100644
index bad6781e81..0000000000
--- a/tensorflow/src/conform/tf.rs
+++ /dev/null
@@ -1,272 +0,0 @@
-#![allow(dead_code)]
-
-use std::{fs, path};
-
-use tensorflow as tf;
-use tensorflow::DataType;
-use tensorflow::FetchToken;
-use tensorflow::Graph;
-use tensorflow::Session;
-use tensorflow::SessionRunArgs;
-
-use tract_hir::internal::*;
-use tract_ndarray::prelude::*;
-
-use std::collections::HashMap;
-use std::collections::HashSet;
-
-pub struct Tensorflow {
-    graph: Graph,
-}
-
-pub fn version() -> String {
-    tf::version().unwrap()
-}
-
-pub fn for_path<P: AsRef<path::Path>>(p: P) -> TractResult<Tensorflow> {
-    use std::io::Read;
-    let mut model = vec![];
-    fs::File::open(p)?.read_to_end(&mut model)?;
-    for_slice(&*model)
-}
-
-pub fn for_slice(buf: &[u8]) -> TractResult<Tensorflow> {
-    let mut graph = Graph::new();
-    graph.import_graph_def(buf, &::tensorflow::ImportGraphDefOptions::new())?;
-    Ok(Tensorflow { graph })
-}
-
-enum TensorHolder {
-    Bool(tf::Tensor<bool>),
-    F16(tf::Tensor<::tensorflow::BFloat16>),
-    F32(tf::Tensor<f32>),
-    F64(tf::Tensor<f64>),
-    U8(tf::Tensor<u8>),
-    U16(tf::Tensor<u16>),
-    I8(tf::Tensor<i8>),
-    I16(tf::Tensor<i16>),
-    I32(tf::Tensor<i32>),
-    I64(tf::Tensor<i64>),
-    String(tf::Tensor<i8>),
-}
-
-impl TensorHolder {
-    fn to_tensor<T: ::tensorflow::TensorType + Copy>(m: ArrayD<T>) -> tf::Tensor<T> {
-        let dims: Vec<u64> = m.shape().iter().map(|d| *d as _).collect();
-        let mut tensor = tf::Tensor::<T>::new(&*dims);
-        tensor.copy_from_slice(m.as_slice().unwrap());
-        tensor
-    }
-}
-
-impl From<Tensor> for TensorHolder {
-    fn from(m: Tensor) -> TensorHolder {
-        match m.datum_type() {
-            DatumType::Bool => TensorHolder::Bool(Self::to_tensor(m.into_plain_array().unwrap())),
-            DatumType::F16 => unimplemented!(),
-            DatumType::F32 => TensorHolder::F32(Self::to_tensor(m.into_plain_array().unwrap())),
-            DatumType::F64 => TensorHolder::F64(Self::to_tensor(m.into_plain_array().unwrap())),
-            DatumType::I8 => TensorHolder::I8(Self::to_tensor(m.into_plain_array().unwrap())),
-            DatumType::I16 => TensorHolder::I16(Self::to_tensor(m.into_plain_array().unwrap())),
-            DatumType::I32 => TensorHolder::I32(Self::to_tensor(m.into_plain_array().unwrap())),
-            DatumType::I64 => TensorHolder::I64(Self::to_tensor(m.into_plain_array().unwrap())),
-            DatumType::U8 => TensorHolder::U8(Self::to_tensor(m.into_plain_array().unwrap())),
-            DatumType::U16 => TensorHolder::U16(Self::to_tensor(m.into_plain_array().unwrap())),
-            DatumType::U32 => TensorHolder::U16(Self::to_tensor(m.into_plain_array().unwrap())),
-            DatumType::U64 => TensorHolder::U16(Self::to_tensor(m.into_plain_array().unwrap())),
-            DatumType::QU8(_) => TensorHolder::U8(Self::to_tensor(m.into_plain_array().unwrap())),
-            DatumType::QI8(_) => TensorHolder::I8(Self::to_tensor(m.into_plain_array().unwrap())),
-            DatumType::QI32(_) => TensorHolder::I32(Self::to_tensor(m.into_plain_array().unwrap())),
-            #[cfg(feature = "complex")]
-            DatumType::ComplexI16 => unimplemented!(),
-            #[cfg(feature = "complex")]
-            DatumType::ComplexI32 => unimplemented!(),
-            #[cfg(feature = "complex")]
-            DatumType::ComplexI64 => unimplemented!(),
-            #[cfg(feature = "complex")]
-            DatumType::ComplexF16 => unimplemented!(),
-            #[cfg(feature = "complex")]
-            DatumType::ComplexF32 => unimplemented!(),
-            #[cfg(feature = "complex")]
-            DatumType::ComplexF64 => unimplemented!(),
-            DatumType::TDim => {
-                let dims = m.to_plain_array_view::<TDim>().unwrap();
-                if let Ok(dims) = dims.iter().map(|d| d.to_i32()).collect::<TractResult<Vec<_>>>() {
-                    TensorHolder::I32(Self::to_tensor(arr1(&dims).into_dyn()))
-                } else {
-                    panic!("Streaming used in tensorflow settings")
-                }
-            }
-            DatumType::String => {
-                TensorHolder::String(Self::to_tensor(m.into_plain_array().unwrap()))
-            }
-            DatumType::Blob => TensorHolder::String(Self::to_tensor(m.into_plain_array().unwrap())),
-            _ => panic!("No support for {:?} DT in tensorflow", m.datum_type()),
-        }
-    }
-}
-
-fn tensor_to_array<T: ::tensorflow::TensorType>(tensor: &tf::Tensor<T>) -> TractResult<ArrayD<T>> {
-    let shape: Vec<usize> = tensor.dims().iter().map(|d| *d as _).collect();
-    Ok(Array::from(tensor.into_iter().cloned().collect::<Vec<_>>()).into_shape_with_order(shape)?)
-}
-
-impl Tensorflow {
-    /// Executes the graph in one batch.
-    pub fn run(
-        &mut self,
-        inputs: Vec<(&str, Tensor)>,
-        output_name: &str,
-    ) -> TractResult<Vec<Tensor>> {
-        let tensors: Vec<(&str, TensorHolder)> =
-            inputs.into_iter().map(|(name, mat)| (name, mat.into())).collect();
-
-        let mut step = SessionRunArgs::new();
-        for t in &tensors {
-            let op = self.graph.operation_by_name_required(t.0)?;
-            match t.1 {
-                TensorHolder::Bool(ref it) => step.add_feed(&op, 0, &it),
-                TensorHolder::U8(ref it) => step.add_feed(&op, 0, &it),
-                TensorHolder::U16(ref it) => step.add_feed(&op, 0, &it),
-                TensorHolder::I8(ref it) => step.add_feed(&op, 0, &it),
-                TensorHolder::I16(ref it) => step.add_feed(&op, 0, &it),
-                TensorHolder::I32(ref it) => step.add_feed(&op, 0, &it),
-                TensorHolder::I64(ref it) => step.add_feed(&op, 0, &it),
-                TensorHolder::F16(_) => unimplemented!(),
-                TensorHolder::F32(ref it) => step.add_feed(&op, 0, &it),
-                TensorHolder::F64(ref it) => step.add_feed(&op, 0, &it),
-                TensorHolder::String(ref it) => step.add_feed(&op, 0, &it),
-            }
-        }
-
-        let op = &self.graph.operation_by_name_required(output_name)?;
-        let tokens =
-            (0..op.num_outputs()).map(|ix| step.request_fetch(&op, ix as i32)).collect::<Vec<_>>();
-
-        let mut session = Session::new(&::tensorflow::SessionOptions::new(), &self.graph)?;
-        session.run(&mut step)?;
-
-        tokens
-            .into_iter()
-            .enumerate()
-            .map(|(ix, tok)| {
-                let output_type =
-                    &self.graph.operation_by_name_required(&output_name)?.output_type(ix);
-                convert_output(&mut step, output_type, tok)
-            })
-            .collect()
-    }
-
-    /// Executes the graph in one batch, and returns the output for every node but the inputs.
-    pub fn run_get_many<'a>(
-        &mut self,
-        inputs: Vec<(&'a str, Tensor)>,
-        targets: Vec<&'a str>,
-    ) -> TractResult<HashMap<&'a str, Vec<Tensor>>> {
-        let mut input_pairs: Vec<(&str, TensorHolder)> = Vec::new();
-        let mut excluded = HashSet::new();
-
-        for (name, mat) in inputs {
-            input_pairs.push((name, mat.into()));
-            excluded.insert(name.to_string());
-        }
-
-        let mut step = SessionRunArgs::new();
-        for t in &input_pairs {
-            let op = self.graph.operation_by_name_required(t.0)?;
-            match t.1 {
-                TensorHolder::Bool(ref it) => step.add_feed(&op, 0, &it),
-                TensorHolder::U8(ref it) => step.add_feed(&op, 0, &it),
-                TensorHolder::U16(ref it) => step.add_feed(&op, 0, &it),
-                TensorHolder::I8(ref it) => step.add_feed(&op, 0, &it),
-                TensorHolder::I16(ref it) => step.add_feed(&op, 0, &it),
-                TensorHolder::I32(ref it) => step.add_feed(&op, 0, &it),
-                TensorHolder::I64(ref it) => step.add_feed(&op, 0, &it),
-                TensorHolder::F16(_) => unimplemented!(),
-                TensorHolder::F32(ref it) => step.add_feed(&op, 0, &it),
-                TensorHolder::F64(ref it) => step.add_feed(&op, 0, &it),
-                TensorHolder::String(ref it) => step.add_feed(&op, 0, &it),
-            }
-        }
-
-        let mut tokens = HashMap::new();
-        trace!("Targets: {:?}", targets);
-        for name in targets {
-            if excluded.contains(name) {
-                continue;
-            }
-
-            if let Some(operation) = self.graph.operation_by_name(name)? {
-                // switch only computes one of its outputs. tf explodes during
-                // the call to run() if we registers them
-                if operation.op_type()? == "Switch" {
-                    continue;
-                }
-
-                // this one pretends to have 5 outputs, but has only one
-                if operation.op_type()? == "FusedBatchNorm" {
-                    continue;
-                }
-
-                let outputs = (0..operation.num_outputs())
-                    .map(|ix| step.request_fetch(&operation, ix as i32))
-                    .collect::<Vec<_>>();
-
-                tokens.insert(name, outputs);
-            }
-        }
-        trace!("Generated all output tokens");
-        trace!("{:?}", tokens);
-
-        // Execute the graph using tensorflow.
-        let mut session = Session::new(&::tensorflow::SessionOptions::new(), &self.graph)?;
-        session.run(&mut step)?;
-        trace!("Tensorflow ran succesfully");
-
-        // Return the output for every node.
-        let mut outputs = HashMap::new();
-        for (name, tokens) in tokens {
-            let tensors = tokens
-                .iter()
-                .enumerate()
-                .map(|(ix, tok)| {
-                    let output_type =
-                        &self.graph.operation_by_name_required(&name)?.output_type(ix);
-                    convert_output(&mut step, output_type, *tok)
-                })
-                .collect::<TractResult<Vec<_>>>()?;
-            outputs.insert(name, tensors);
-        }
-
-        Ok(outputs)
-    }
-}
-
-/// Converts the output of a Tensorflow node into a Tensor.
-fn convert_output(
-    step: &mut SessionRunArgs,
-    output_type: &DataType,
-    output: FetchToken,
-) -> TractResult<Tensor> {
-    macro_rules! convert {
-        ($dt:ident) => {
-            match step.fetch(output) {
-                Err(r) => Err(r)?,
-                Ok(output) => tensor_to_array::<$dt>(&output)?.into(),
-            }
-        };
-    };
-
-    let tract_tensor = match output_type {
-        DataType::Bool => convert!(bool),
-        DataType::Float => convert!(f32),
-        DataType::Double => convert!(f64),
-        DataType::UInt8 => convert!(u8),
-        DataType::Int8 => convert!(i8),
-        DataType::Int32 => convert!(i32),
-        DataType::Int64 => convert!(i64),
-        t => bail!("Missing conversion for tensorflow to tract (type: {:?})", t),
-    };
-
-    Ok(tract_tensor)
-}
diff --git a/tensorflow/src/lib.rs b/tensorflow/src/lib.rs
index 30e17e08ac..752d746b77 100644
--- a/tensorflow/src/lib.rs
+++ b/tensorflow/src/lib.rs
@@ -43,13 +43,8 @@ extern crate log;
 extern crate env_logger;
 extern crate prost;
 extern crate prost_types;
-#[cfg(feature = "conform")]
-extern crate tensorflow;
 pub extern crate tract_hir;
 
-#[cfg(feature = "conform")]
-pub mod conform;
-
 pub mod model;
 pub mod ops;
 pub mod tensor;
diff --git a/test-rt/test-cuda/Cargo.toml b/test-rt/test-cuda/Cargo.toml
index 962080a06e..313572f014 100644
--- a/test-rt/test-cuda/Cargo.toml
+++ b/test-rt/test-cuda/Cargo.toml
@@ -27,7 +27,7 @@ log.workspace = true
 tract-core.workspace = true
 tract-onnx-opl.workspace = true
 infra = { path = "../infra" }
-tract-cuda.workspace = true
+tract-cuda = { workspace = true, features = ["cuda-13000"] }
 tract-gpu.workspace = true
 suite-onnx = { path = "../suite-onnx" }
 suite-unit = { path = "../suite-unit" }
diff --git a/tflite/Cargo.toml b/tflite/Cargo.toml
index d323e8a5e5..e2e9765953 100644
--- a/tflite/Cargo.toml
+++ b/tflite/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-tflite"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 authors = ["Mathieu Poumeyrol <kali@zoy.org>"]
 license = "MIT OR Apache-2.0"
 description = "Tiny, no-nonsense, self contained, TensorFlow and ONNX inference"
diff --git a/transformers/Cargo.toml b/transformers/Cargo.toml
index eb63749c98..9ab031bbe4 100644
--- a/transformers/Cargo.toml
+++ b/transformers/Cargo.toml
@@ -1,6 +1,6 @@
 [package]
 name = "tract-transformers"
-version = "0.23.0-pre"
+version = "0.23.1-pre"
 license = "MIT OR Apache-2.0"
 authors = ["Mathieu Poumeyrol <kali@zoy.org>", "Louis Chouraki <louis.chouraki@sonos.com>"]
 description = "Tiny, no-nonsense, self contained, TensorFlow and ONNX inference"
diff --git a/transformers/src/ops/diag_gather.rs b/transformers/src/ops/diag_gather.rs
index ad8f61b16b..678831dc23 100644
--- a/transformers/src/ops/diag_gather.rs
+++ b/transformers/src/ops/diag_gather.rs
@@ -142,7 +142,7 @@ impl TypedOp for DiagGather {
         Ok(Some(tvec![Some(input_roi)]))
     }
 
-    fn substitute_symbols(
+    fn set_symbols(
         &self,
         _source: &TypedModel,
         node: &TypedNode,