diff --git a/tests/model_executor/test_eagle_quantization.py b/tests/model_executor/test_eagle_quantization.py
index 1203aef6a..519a48cae 100644
--- a/tests/model_executor/test_eagle_quantization.py
+++ b/tests/model_executor/test_eagle_quantization.py
@@ -139,6 +139,51 @@ def test_maybe_remap_kv_scale_name():
     assert remapped in params_dict or remapped == name or remapped is None
 
 
+def test_eagle3_lm_head_receives_quant_config():
+    """Eagle3LlamaForCausalLM must pass quant_config to ParallelLMHead.
+
+    Without quant_config, quantized lm_head weights (e.g. INT8 per-channel)
+    in Eagle3 drafter checkpoints fail to load because ParallelLMHead doesn't
+    expect weight_packed tensors.
+    """
+    from vllm.model_executor.models.llama_eagle3 import Eagle3LlamaForCausalLM
+
+    mock_quant_config = Mock()
+
+    mock_hf_config = Mock()
+    mock_hf_config.draft_vocab_size = 1000
+    mock_hf_config.hidden_size = 256
+    mock_hf_config.vocab_size = 32000
+    mock_hf_config.logit_scale = 1.0
+
+    mock_vllm_config = Mock()
+    mock_vllm_config.speculative_config.draft_model_config.hf_config = mock_hf_config
+    mock_vllm_config.model_config.get_num_layers.return_value = 32
+    mock_vllm_config.speculative_config.parallel_drafting = False
+
+    with (
+        patch("vllm.model_executor.models.llama_eagle3.LlamaModel") as MockModel,
+        patch("vllm.model_executor.models.llama_eagle3.ParallelLMHead") as MockLMHead,
+        patch("vllm.model_executor.models.llama_eagle3.LogitsProcessor"),
+        patch(
+            "vllm.model_executor.models.llama_eagle3.get_draft_quant_config",
+            return_value=mock_quant_config,
+        ),
+    ):
+        MockModel.return_value.use_aux_hidden_state = True
+
+        Eagle3LlamaForCausalLM(vllm_config=mock_vllm_config)
+
+        MockLMHead.assert_called_once()
+        call_kwargs = MockLMHead.call_args.kwargs
+        assert "quant_config" in call_kwargs, (
+            "ParallelLMHead must receive quant_config for quantized lm_head weights"
+        )
+        assert call_kwargs["quant_config"] is mock_quant_config, (
+            "ParallelLMHead must receive the draft model's quant_config"
+        )
+
+
 def test_load_weights_kv_scale_handling():
     kv_scale_param = Mock()
     kv_scale_param.weight_loader = Mock()
diff --git a/vllm/model_executor/models/llama_eagle3.py b/vllm/model_executor/models/llama_eagle3.py
index 462d18c98..fcec4a4d8 100644
--- a/vllm/model_executor/models/llama_eagle3.py
+++ b/vllm/model_executor/models/llama_eagle3.py
@@ -294,6 +294,7 @@ class Eagle3LlamaForCausalLM(LlamaForCausalLM):
         self.lm_head = ParallelLMHead(
             self.config.draft_vocab_size,
             self.config.hidden_size,
+            quant_config=get_draft_quant_config(vllm_config),
             prefix=maybe_prefix(prefix, "lm_head"),
         )
         self.logits_processor = LogitsProcessor(
diff --git a/vllm/v1/spec_decode/eagle.py b/vllm/v1/spec_decode/eagle.py
index 4b20413ca..f331e68fb 100644
--- a/vllm/v1/spec_decode/eagle.py
+++ b/vllm/v1/spec_decode/eagle.py
@@ -1390,6 +1390,8 @@ class SpecDecodeBaseProposer:
                 )
             elif (
                 hasattr(target_language_model, "lm_head")
+                and hasattr(target_language_model.lm_head, "weight")
+                and hasattr(self.model.lm_head, "weight")
                 and isinstance(target_language_model.lm_head.weight, torch.Tensor)
                 and isinstance(self.model.lm_head.weight, torch.Tensor)
                 # TODO: Offload to CPU for comparison to avoid extra GPU memory