diff --git a/python/sglang/srt/model_loader/weight_utils.py b/python/sglang/srt/model_loader/weight_utils.py
index d1c44e4f7..e61a521e1 100644
--- a/python/sglang/srt/model_loader/weight_utils.py
+++ b/python/sglang/srt/model_loader/weight_utils.py
@@ -34,6 +34,7 @@ from sglang.srt.configs.load_config import LoadConfig
 from sglang.srt.configs.model_config import ModelConfig
 from sglang.srt.distributed import get_tensor_model_parallel_rank
 from sglang.srt.layers.quantization import QuantizationConfig, get_quantization_config
+from sglang.srt.layers.quantization.modelopt_quant import ModelOptFp4Config
 from sglang.srt.utils import print_warning_once
 
 logger = logging.getLogger(__name__)
@@ -206,7 +207,10 @@ def get_quant_config(
             config["adapter_name_or_path"] = model_name_or_path
         elif model_config.quantization == "modelopt":
             if config["producer"]["name"] == "modelopt":
-                return quant_cls.from_config(config)
+                if "FP4" in config["quantization"]["quant_algo"]:
+                    return ModelOptFp4Config.from_config(config)
+                else:
+                    return quant_cls.from_config(config)
             else:
                 raise ValueError(
                     f"Unsupported quantization config"
diff --git a/python/sglang/srt/models/deepseek_v2.py b/python/sglang/srt/models/deepseek_v2.py
index 041ecc18c..192ab50ed 100644
--- a/python/sglang/srt/models/deepseek_v2.py
+++ b/python/sglang/srt/models/deepseek_v2.py
@@ -1926,6 +1926,8 @@ class DeepseekV2ForCausalLM(nn.Module):
         if (
             deep_gemm_wrapper.ENABLE_JIT_DEEPGEMM
             and deep_gemm_wrapper.DEEPGEMM_SCALE_UE8M0
+            and hasattr(self.quant_config, "weight_block_size")
+            and self.quant_config.weight_block_size is not None
         ):
             self._weight_requant_ue8m0()
 
@@ -2158,12 +2160,9 @@ class DeepseekV2ForCausalLM(nn.Module):
                             "k_scale" in name or "v_scale" in name
                         ) and name not in params_dict:
                             # modelopt attn kv scale is named differently
-                            if any(scale in name for scale in ["k_scale", "v_scale"]):
-                                name = name.replace("_proj", "attn_mqa")
-                            else:
-                                logger.warning(
-                                    f"Unknown scale found in checkpoint: {name}"
-                                )
+                            for scale in ["k_scale", "v_scale"]:
+                                if scale in name:
+                                    name = name.replace(f"{scale[0]}_proj", "attn_mqa")
                         param = params_dict[name]
                         weight_loader = getattr(
                             param, "weight_loader", default_weight_loader