端口错开后依旧有如上报错
启动命令
nohup vllm serve /root/vllm/Qwen/Qwen3.6-35B-A3B/ \
--host 0.0.0.0 \
--port 8000 \
--served-model-name qwen3.6 \
--dtype bfloat16 \
--trust-remote-code \
--tensor-parallel-size 4 \
--distributed-executor-backend mp \
--gpu-memory-utilization 0.8 \
--max-model-len 32768 \
--max-num-batched-tokens 131072 \
--max-num-seqs 128 \
--enable-chunked-prefill \
--enable-prefix-caching \
qwen.log 2>&1 &
nohup vllm serve /root/vllm/bge-m3/ \
--host 0.0.0.0 \
--port 8001 \
--served-model-name bge-m3 \
--tensor-parallel-size 1 \
--gpu-memory-utilization 0.1 \
--trust-remote-code \
--dtype auto \
bge-m3.log 2>&1 &
报错日志：
(EngineCore pid=26596) INFO 05-23 16:26:48 [core.py:105] Initializing a V1 LLM engine (v0.19.0) with config: model='/root/vllm/bge-m3/', speculative_config=None, tokenizer='/root/vllm/bge-m3/', skip_toke
nizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.float16, max_seq_len=8192, download_dir=None, load_format=auto, tensor_parallel_size=1,
pipeline_parallel_size=1, data_parallel_size=1, decode_context_parallel_size=1, dcp_comm_backend=ag_rs, disable_custom_all_reduce=True, quantization=None, enforce_eager=False, enable_return_routed_expert
s=False, kv_cache_dtype=auto, device_config=cuda, structured_outputs_config=StructuredOutputsConfig(backend='auto', disable_any_whitespace=False, disable_additional_properties=False, reasoning_parser='',
reasoning_parser_plugin='', enable_in_reasoning=False), observability_config=ObservabilityConfig(show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, kv_cache_m
etrics=False, kv_cache_metrics_sample=0.01, cudagraph_metrics=False, enable_layerwise_nvtx_tracing=False, enable_mfu_metrics=False, enable_mm_processor_stats=False, enable_logging_iteration_details=False
), seed=0, served_model_name=bge-m3, enable_prefix_caching=False, enable_chunked_prefill=False, pooler_config=PoolerConfig(task=None, pooling_type=None, seq_pooling_type='CLS', tok_pooling_type='ALL', us
e_activation=True, dimensions=None, enable_chunked_processing=False, max_embed_len=None, logit_bias=None, step_tag_id=None, returned_token_ids=None), compilation_config={'mode': <CompilationMode.VLLM_COM
PILE: 3>, 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['none'], 'splitting_ops': ['vllm::unified_attention', 'vllm::unified_atten
tion_with_output', 'vllm::unified_mla_attention', 'vllm::unified_mla_attention_with_output', 'vllm::mamba_mixer2', 'vllm::mamba_mixer', 'vllm::short_conv', 'vllm::linear_attention', 'vllm::plamo2_mamba_m
ixer', 'vllm::gdn_attention_core', 'vllm::olmo_hybrid_gdn_full_forward', 'vllm::kda_attention', 'vllm::sparse_attn_indexer', 'vllm::rocm_aiter_sparse_attn_indexer', 'vllm::mx_sparse_attn_indexer', 'vllm:
:mx_sparse_attn_indexer_bf16', 'vllm::unified_kv_cache_update', 'vllm::unified_mla_kv_cache_update'], 'compile_mm_encoder': False, 'cudagraph_mm_encoder': False, 'encoder_cudagraph_token_budgets': [], 'e
ncoder_cudagraph_max_images_per_batch': 0, 'compile_sizes': [], 'compile_ranges_endpoints': [8192], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'size_asserts': False, 'alignment_a
sserts': False, 'scalar_asserts': False}, 'inductor_passes': {}, 'cudagraph_mode': <CUDAGraphMode.PIECEWISE: 1>, 'cudagraph_num_of_warmups': 1, 'cudagraph_capture_sizes': [1, 2, 4, 8, 16, 24, 32, 40, 48,
56, 64, 72, 80, 88, 96, 104, 112, 120, 128, 136, 144, 152, 160, 168, 176, 184, 192, 200, 208, 216, 224, 232, 240, 248, 256, 272, 288, 304, 320, 336, 352, 368, 384, 400, 416, 432, 448, 464, 480, 496, 512
], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': False, 'fuse_act_quant': False, 'fuse_attn_quant': False, '
enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False}, 'max_cudagraph_capture_size': 512, 'dynamic_shapes_config': {'type': <DynamicShapesType.BACKED: 'backed'>, 'evaluate_guards': Fa
lse, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': True, 'static_all_moe_layers': []}
(EngineCore pid=26596) INFO 05-23 16:26:48 [parallel_state.py:1400] world_size=1 rank=0 local_rank=0 distributed_init_method=tcp://10.217.247.136:40835 backend=nccl
(EngineCore pid=26596) INFO 05-23 16:26:48 [parallel_state.py:1716] rank 0 in world size 1 is assigned as DP rank 0, PP rank 0, PCP rank 0, TP rank 0, EP rank N/A, EPLB rank N/A
[16:26:59.536][MXKW][E]queues.c :826 : [mxkwCreateQueueBlock][Hint]ioctl create queue block timeout, gpu_id:65475 type:21. Retrying.
[16:27:09.776][MXKW][E]queues.c :826 : [mxkwCreateQueueBlock][Hint]ioctl create queue block timeout, gpu_id:65475 type:21. Retrying.
[16:27:20.016][MXKW][E]queues.c :826 : [mxkwCreateQueueBlock][Hint]ioctl create queue block timeout, gpu_id:65475 type:21. Retrying.
[16:27:30.256][MXKW][E]queues.c :826 : [mxkwCreateQueueBlock][Hint]ioctl create queue block timeout, gpu_id:65475 type:21. Retrying.
[16:27:40.496][MXKW][E]queues.c :826 : [mxkwCreateQueueBlock][Hint]ioctl create queue block timeout, gpu_id:65475 type:21. Retrying.
[16:27:50.736][MXKW][E]queues.c :826 : [mxkwCreateQueueBlock][Hint]ioctl create queue block timeout, gpu_id:65475 type:21. Retrying.
[16:28:00.977][MXKW][E]queues.c :826 : [mxkwCreateQueueBlock][Hint]ioctl create queue block timeout, gpu_id:65475 type:21. Retrying.