[MODEL] support lfm2

README.md

@@ -20,7 +20,7 @@
 </p>
 
 ## Latest News
-
+* 01/07/2026 7.1.0-dev `main`: ✨ Added `lfm2` model support
 * 06/30/2026 7.1.0-dev `main`: ✨ Added `minimax_m3_vl` / MiniMax M3 model support
 * 06/25/2026 7.1.0-dev `main`: ✨ Added `cohere2_moe` model support
 * 05/25/2026 7.1.0-dev `main`: ✨ Added `hy_3` and `ministral3` model support
@@ -267,7 +267,7 @@ Selected public references where teams or companies explicitly mention GPT-QMode
 | Dream                    | ✅ | GRIN-MoE                        | ✅ | Instella         | ✅ | Phi 1-4                         | ✅ | Voxtral                | ✅ |
 | ERNIE 4.5 / MoE / VL MoE | ✅ | GLM 4/4V/4.5V/4.6V/5/5.1/OCR/ASR | ✅ | GLM4 MoE / Lite / 4.5V MoE | ✅ | MiniCPM 3/O/V/V 4_6             | ✅ | PanGu-α                | ✅ |
 | XVERSE                   | ✅ | Brumby                          | ✅ | Hymba            | ✅ | Mistral                         | ✅ | Qwen 1/2/3/3.5         | ✅ |
-| MiniMax M2/M3            | ✅ | AfMoE                           | ✅ | Bailing-MoE      | ✅ | LFM2-MoE                        | ✅ | Marin                  | ✅ |
+| MiniMax M2/M3            | ✅ | AfMoE                           | ✅ | Bailing-MoE      | ✅ | LFM2 / LFM2-MoE                 | ✅ | Marin                  | ✅ |
 | InternVL Chat            | ✅ | Laguna                          | ✅ | Mimo / Mimo V2   | ✅ | Zamba / Zamba2                  | ✅ | Intern S1              | ✅ |
 | HunYuan V1 Dense / MoE   | ✅ | HY-V3                           | ✅ |    |  |                  |  |                |   |
 

gptqmodel/models/auto.py

@@ -128,6 +128,7 @@
 from .definitions.klear import KlearQModel  # noqa: E402
 from .definitions.kimi_k25 import KimiK25QModel  # noqa: E402
 from .definitions.laguna import LagunaQModel  # noqa: E402
+from .definitions.lfm2 import LFM2QModel  # noqa: E402
 from .definitions.lfm2_moe import LFM2MoeQModel  # noqa: E402
 from .definitions.llada2 import LLaDA2MoeQModel
 from .definitions.llama import LlamaQModel  # noqa: E402
@@ -333,6 +334,7 @@
     "nemotronh_nano_omni_reasoning_v3": NemotronOmniQModel,
     "bailing_moe": BailingMoeQModel,
     "bailing_hybrid": BailingMoeQModel,
+    "lfm2": LFM2QModel,
     "lfm2_moe": LFM2MoeQModel,
     "llada2_moe": LLaDA2MoeQModel,
     "mistral3": Mistral3GPTQ,

gptqmodel/models/definitions/lfm2.py

@@ -0,0 +1,30 @@
+# SPDX-FileCopyrightText: 2026 ModelCloud.ai
+# SPDX-FileCopyrightText: 2026 qubitium@modelcloud.ai
+# SPDX-License-Identifier: Apache-2.0
+# Contact: qubitium@modelcloud.ai, x.com/qubitium
+
+from ..base import BaseQModel
+
+
+class LFM2QModel(BaseQModel):
+    pre_lm_head_norm_module = "model.embedding_norm"
+
+    layer_modules_strict = False
+
+    module_tree = [
+        "model",
+        "layers",
+        "#",
+        {
+            "operator_norm": ("operator_norm:!",),
+            "conv": ("in_proj", "out_proj"),
+            "self_attn": (
+                "q_proj:0",
+                "k_proj:0",
+                "v_proj:0",
+                "out_proj:1",
+            ),
+            "ffn_norm": ("ffn_norm:!",),
+            "feed_forward": ("w1:0", "w3:0", "w2:1"),
+        },
+    ]

tests/models/test_lfm2.py

@@ -0,0 +1,32 @@
+# SPDX-FileCopyrightText: 2026 ModelCloud.ai
+# SPDX-FileCopyrightText: 2026 qubitium@modelcloud.ai
+# SPDX-License-Identifier: Apache-2.0
+# Contact: qubitium@modelcloud.ai, x.com/qubitium
+
+from model_test import ModelTest
+
+
+class TestLFM2(ModelTest):
+    NATIVE_MODEL_ID = "/monster/data/model/LFM2.5-1.2B-Instruct" # "LiquidAI/LFM2.5-1.2B-Instruct"
+    TRUST_REMOTE_CODE = False
+    USE_FLASH_ATTN = False
+    GROUP_SIZE = 32
+    DATASET_SIZE = 512
+    EVAL_BATCH_SIZE = 4
+    EVAL_TASKS_SLOW = {
+        "arc_challenge": {
+            "chat_template": True,
+            "acc": {
+                "value": 0.3780,
+                "floor_pct": 0.04,
+            },
+            "acc_norm": {
+                "value": 0.3968,
+                "floor_pct": 0.04,
+            },
+        },
+    }
+    EVAL_TASKS_FAST = ModelTest.derive_fast_eval_tasks(EVAL_TASKS_SLOW)
+
+    def test_lfm2(self):
+        self.quantize_and_evaluate()