[ModelOpt][PP] Keep BF16 shared experts out of the NVFP4 fusion so TP1 pipeline stages can load (#40628)

python/sglang/srt/layers/quantization/modelopt_quant.py

@@ -1497,6 +1497,15 @@ class ModelOptFp4Config(ModelOptQuantConfig):
     def get_min_capability(cls) -> int:
         return 80
 
+    def can_fuse_shared_expert(self) -> bool:
+        # A shared-expert body kept BF16 via exclude_modules cannot share the packed
+        # FP4 FusedMoE buffers. The shared_expert_gate is a separate linear (kept
+        # BF16 by e.g. Qwen3-Next NVFP4 checkpoints) and must not veto fusion.
+        return not any(
+            "shared_expert" in name and "shared_expert_gate" not in name
+            for name in self.exclude_modules
+        )
+
     @staticmethod
     def common_group_size(cfg: dict) -> int:
         """Return the unique group_size across the config; raise if missing/mismatched."""

test/registered/unit/layers/quantization/test_modelopt_nvfp4.py

@@ -132,6 +132,28 @@ class TestModelOptNvfp4(CustomTestCase):
                 use_per_token_activation=True,
             )
 
+    def test_shared_expert_fusion_requires_matching_fp4_precision(self):
+        quantized_shared = ModelOptFp4Config(
+            is_checkpoint_nvfp4_serialized=True,
+            group_size=16,
+        )
+        bf16_shared = ModelOptFp4Config(
+            is_checkpoint_nvfp4_serialized=True,
+            group_size=16,
+            exclude_modules=["model.layers.*.mlp.shared_experts*"],
+        )
+
+        gate_only_bf16 = ModelOptFp4Config(
+            is_checkpoint_nvfp4_serialized=True,
+            group_size=16,
+            exclude_modules=["model.layers.*.mlp.shared_expert_gate"],
+        )
+
+        self.assertTrue(quantized_shared.can_fuse_shared_expert())
+        self.assertFalse(bf16_shared.can_fuse_shared_expert())
+        # Only the gate is BF16 (Qwen3-Next NVFP4): the FP4 body still fuses.
+        self.assertTrue(gate_only_bf16.can_fuse_shared_expert())
+
 
 if __name__ == "__main__":
     unittest.main()