diff --git a/python/pyproject.toml b/python/pyproject.toml
index ea55f93c0..caf41a2d8 100644
--- a/python/pyproject.toml
+++ b/python/pyproject.toml
@@ -19,7 +19,7 @@ dependencies = [
 
 [project.optional-dependencies]
 srt = ["aiohttp", "fastapi", "psutil", "rpyc", "torch", "uvloop", "uvicorn",
-       "zmq", "vllm>=0.2.5", "interegular", "lark", "numba",
+       "zmq", "vllm>=0.3.3", "interegular", "lark", "numba",
        "pydantic", "referencing", "diskcache", "cloudpickle", "pillow", "outlines>=0.0.27"]
 openai = ["openai>=1.0", "numpy"]
 anthropic = ["anthropic", "numpy"]
diff --git a/python/sglang/srt/models/qwen.py b/python/sglang/srt/models/qwen.py
index 114aec717..111ad704b 100644
--- a/python/sglang/srt/models/qwen.py
+++ b/python/sglang/srt/models/qwen.py
@@ -5,6 +5,7 @@ from sglang.srt.layers.logits_processor import LogitsProcessor
 from sglang.srt.layers.radix_attention import RadixAttention
 from sglang.srt.managers.router.model_runner import InputMetadata
 from torch import nn
+from transformers import PretrainedConfig
 from vllm.model_executor.layers.activation import SiluAndMul
 from vllm.model_executor.layers.layernorm import RMSNorm
 from vllm.model_executor.layers.linear import (
@@ -25,7 +26,6 @@ from vllm.model_executor.weight_utils import (
     default_weight_loader,
     hf_model_weights_iterator,
 )
-from vllm.transformers_utils.configs.qwen import QWenConfig
 
 
 class QWenMLP(nn.Module):
@@ -130,7 +130,7 @@ class QWenAttention(nn.Module):
 
 
 class QWenBlock(nn.Module):
-    def __init__(self, config: QWenConfig, layer_id, linear_method=None):
+    def __init__(self, config: PretrainedConfig, layer_id, linear_method=None):
         super().__init__()
         self.ln_1 = RMSNorm(config.hidden_size, eps=config.layer_norm_epsilon)
 
@@ -179,7 +179,7 @@ class QWenBlock(nn.Module):
 
 
 class QWenModel(nn.Module):
-    def __init__(self, config: QWenConfig, linear_method=None):
+    def __init__(self, config: PretrainedConfig, linear_method=None):
         super().__init__()
         self.config = config
         self.vocab_size = config.vocab_size
@@ -216,7 +216,7 @@ class QWenModel(nn.Module):
 
 
 class QWenLMHeadModel(nn.Module):
-    def __init__(self, config: QWenConfig, linear_method=None):
+    def __init__(self, config: PretrainedConfig, linear_method=None):
         super().__init__()
         self.config = config
         self.transformer = QWenModel(config, linear_method=linear_method)