(APIServer pid=331487) INFO 2026-09-22T04:09:23Z [api_utils.py:347] (APIServer pid=331487) INFO 2026-09-22T04:09:23Z [api_utils.py:347] █ █ █▄ ▄█ (APIServer pid=331487) INFO 2026-09-22T04:09:23Z [api_utils.py:347] ▄▄ ▄█ █ █ █ ▀▄▀ █ version 0.29.0 (APIServer pid=331487) INFO 2026-09-22T04:09:23Z [api_utils.py:347] █▄█▀ █ █ █ █ model /workshop/hf-cache/hub/models--openjev--openjev-FP8/snapshots/4ec320f267401e67c9be04d5df1be4d2b6b64f10 (APIServer pid=331487) INFO 2026-09-22T04:09:23Z [api_utils.py:347] ▀▀ ▀▀▀▀▀ ▀▀▀▀▀ ▀ ▀ (APIServer pid=331487) INFO 2026-09-22T04:09:23Z [api_utils.py:347] (APIServer pid=331487) INFO 2026-09-22T04:09:23Z [api_utils.py:286] non-default args: {'model_tag': '/workshop/hf-cache/hub/models--openjev--openjev-FP8/snapshots/4ec320f267401e67c9be04d5df1be4d2b6b64f10', 'host': '127.0.0.1', 'model': '/workshop/hf-cache/hub/models--openjev--openjev-FP8/snapshots/4ec320f267401e67c9be04d5df1be4d2b6b64f10', 'trust_remote_code': True, 'max_model_len': 16384, 'quantization': 'fp8', 'max_logprobs': 64, 'served_model_name': ['openjev-fp8-largecard'], 'gpu_memory_utilization': 0.9, 'enable_prefix_caching': True, 'limit_mm_per_prompt': {'image': 0}, 'max_num_seqs': 1, 'gdn_prefill_backend': 'triton'} (APIServer pid=331487) INFO 2026-09-22T04:09:23Z [model.py:684] Resolved architecture: Qwen3_5ForConditionalGeneration (APIServer pid=331487) INFO 2026-09-22T04:09:23Z [model.py:2021] Using max model len 16384 (APIServer pid=331487) INFO 2026-09-22T04:09:26Z [scheduler.py:277] Chunked prefill is enabled with max_num_batched_tokens=8192. (APIServer pid=331487) INFO 2026-09-22T04:09:26Z [config.py:625] Mamba cache mode is set to 'align' for Qwen3_5ForConditionalGeneration by default when prefix caching is enabled (APIServer pid=331487) WARNING 2026-09-22T04:09:26Z [vllm.py:1211] Auto-disabled DeepGemm for model_type=qwen3_5_text on Blackwell. DeepGemm E8M0 scale format causes accuracy degradation for this architecture. Falling back to CUTLASS. To disable DeepGemm globally, set VLLM_USE_DEEP_GEMM=0. (APIServer pid=331487) INFO 2026-09-22T04:09:26Z [kernel.py:369] Final IR op priority after setting platform defaults: IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']) (APIServer pid=331487) INFO 2026-09-22T04:09:26Z [compilation.py:329] Enabled custom fusions: norm_quant, act_quant (APIServer pid=331487) [transformers] The `use_fast` parameter is deprecated and will be removed in a future version. Use `backend="torchvision"` instead of `use_fast=True`, or `backend="pil"` instead of `use_fast=False`. (EngineCore pid=332027) INFO 2026-09-22T04:09:45Z [core.py:123] Initializing a V1 LLM engine (v0.29.0) with config: model='/workshop/hf-cache/hub/models--openjev--openjev-FP8/snapshots/4ec320f267401e67c9be04d5df1be4d2b6b64f10', speculative_config=None, tokenizer='/workshop/hf-cache/hub/models--openjev--openjev-FP8/snapshots/4ec320f267401e67c9be04d5df1be4d2b6b64f10', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=16384, 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=False, quantization=fp8, quantization_config=None, enforce_eager=False, enable_return_routed_experts=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, per_request_spec_decode_metrics='none', kv_cache_metrics=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, jit_monitor_mode='warn', jit_monitor_verbose=False), seed=0, served_model_name=openjev-fp8-largecard, enable_prefix_caching=True, enable_chunked_prefill=True, pooler_config=None, compilation_config={'mode': , 'debug_dump_path': None, 'cache_dir': '', 'compile_cache_save_format': 'binary', 'backend': 'inductor', 'custom_ops': ['+quant_fp8', 'none', '+quant_fp8'], 'ir_enable_torch_wrap': True, 'splitting_ops': ['vllm::unified_attention_with_output', 'vllm::unified_mla_attention_with_output', 'vllm::mamba_mixer2', 'vllm::mamba_mixer', 'vllm::short_conv', 'vllm::qwen4_exp_compute_ple_ngram_ids', 'vllm::qwen4_exp_ple_short_conv', 'vllm::qwen4_exp_qsa_with_output', 'vllm::linear_attention', 'vllm::qwen_gdn_attention_core', 'vllm::qwen_gdn_attention_core_fused_norm_packed', 'vllm::gdn_attention_core_xpu', 'vllm::olmo_hybrid_gdn_full_forward', 'vllm::sparse_attn_indexer', 'vllm::rocm_aiter_sparse_attn_indexer', 'vllm::deepseek_v4_attention', 'vllm::hpc_rope_norm_forward', 'vllm::unified_kv_cache_update', 'vllm::unified_mla_kv_cache_update'], 'compile_mm_encoder': False, 'cudagraph_mm_encoder': False, 'encoder_cudagraph_token_budgets': [], 'encoder_cudagraph_max_vision_items_per_batch': 0, 'encoder_cudagraph_max_frames_per_batch': None, 'compile_sizes': [], 'compile_ranges_endpoints': [8192], 'inductor_compile_config': {'enable_auto_functionalized_v2': False, 'combo_kernels': True, 'benchmark_combo_kernel': True}, 'inductor_passes': {}, 'cudagraph_mode': , 'cudagraph_num_of_warmups': 1, 'cudagraph_capture_sizes': [1, 2], 'cudagraph_copy_inputs': False, 'cudagraph_specialize_lora': True, 'use_inductor_graph_partition': False, 'pass_config': {'fuse_norm_quant': True, 'fuse_act_quant': True, 'fuse_attn_quant': False, 'enable_sp': False, 'fuse_gemm_comms': False, 'fuse_allreduce_rms': False, 'enable_qk_norm_rope_fusion': False, 'fuse_rope_kvcache_cat_mla': False, 'fuse_act_padding': False, 'fuse_qk_norm_rope_kvcache': False}, 'max_cudagraph_capture_size': 2, 'dynamic_shapes_config': {'type': , 'evaluate_guards': False, 'assume_32_bit_indexing': False}, 'local_cache_dir': None, 'fast_moe_cold_start': False, 'static_all_moe_layers': []}, kernel_config=KernelConfig(ir_op_priority=IrOpPriorityConfig(rms_norm=['native'], fused_add_rms_norm=['native']), enable_flashinfer_autotune=True, enable_cutedsl_warmup=True, enable_jit_warmup=True, enable_bf16x3_router_gemm=False, moe_backend='auto', linear_backend='auto') (EngineCore pid=332027) INFO 2026-09-22T04:09:48Z [parallel_state.py:1775] world_size=1 rank=0 local_rank=0 distributed_init_method=file:///tmp/vllm_dist_db63527628864e0ebc4531fbbfd6283f backend=nccl (EngineCore pid=332027) INFO 2026-09-22T04:09:48Z [parallel_state.py:2119] 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 (EngineCore pid=332027) INFO 2026-09-22T04:09:48Z [gpu_worker.py:429] Using V2 Model Runner (EngineCore pid=332027) INFO 2026-09-22T04:09:48Z [model_runner.py:382] Loading model from scratch... (EngineCore pid=332027) INFO 2026-09-22T04:09:49Z [cuda.py:551] Using backend AttentionBackendEnum.FLASH_ATTN for vit attention (EngineCore pid=332027) INFO 2026-09-22T04:09:49Z [mm_encoder_attention.py:372] Using AttentionBackendEnum.FLASH_ATTN for MMEncoderAttention. (EngineCore pid=332027) INFO 2026-09-22T04:09:49Z [__init__.py:695] Selected CutlassFp8BlockScaledMMKernel for Fp8LinearMethod (EngineCore pid=332027) INFO 2026-09-22T04:09:49Z [qwen_gdn_linear_attn.py:167] Using Triton/FLA GDN prefill kernel (requested=triton, head_k_dim=128). (EngineCore pid=332027) INFO 2026-09-22T04:09:49Z [qwen_gdn_linear_attn.py:519] GDN decode kernel: cuda (EngineCore pid=332027) INFO 2026-09-22T04:09:49Z [cuda.py:492] Using FLASH_ATTN attention backend out of potential backends: ['FLASH_ATTN', 'FLASHINFER', 'TRITON_ATTN', 'FLEX_ATTENTION']. (EngineCore pid=332027) INFO 2026-09-22T04:09:49Z [flash_attn.py:897] Using FlashAttention version 2 (EngineCore pid=332027) INFO 2026-09-22T04:09:50Z [weight_utils.py:863] Filesystem type for checkpoints: EXT4. Checkpoint size: 28.30 GiB. Available RAM: 112.08 GiB. (EngineCore pid=332027) INFO 2026-09-22T04:09:50Z [weight_utils.py:886] Auto-prefetch is disabled because the filesystem (EXT4) is not a recognized network FS (NFS/Lustre). If you want to force prefetching, start vLLM with --safetensors-load-strategy=prefetch. (EngineCore pid=332027) Loading safetensors checkpoint shards: 0% Completed | 0/12 [00:00= mamba page size. (EngineCore pid=332027) INFO 2026-09-22T04:10:02Z [interface.py:942] Padding mamba page size by 0.13% to ensure that mamba page size and attention page size are exactly equal. (EngineCore pid=332027) INFO 2026-09-22T04:10:02Z [utils.py:306] Using LBNHC KV cache layout. (EngineCore pid=332027) [transformers] The `use_fast` parameter is deprecated and will be removed in a future version. Use `backend="torchvision"` instead of `use_fast=True`, or `backend="pil"` instead of `use_fast=False`. (EngineCore pid=332027) [transformers] Qwen3VL video processing does not apply the per-frame pixel cap the reference implementation (qwen-vl-utils) applies, so some videos cost far more tokens than they would there. In v5.22 the capped behavior will become the default and `cap_pixels_per_frame` will be removed. Pass `cap_pixels_per_frame=True` to adopt the reference behavior now, or `False` to keep the current behavior and silence this warning. (EngineCore pid=332027) INFO 2026-09-22T04:10:11Z [encoder_runner.py:131] Encoder cache will be initialized with a budget of 12288 tokens, and profiled with 1 video items of the maximum feature size. (EngineCore pid=332027) INFO 2026-09-22T04:10:32Z [backends.py:1094] Using cache directory: /workshop/.cache/vllm/torch_compile_cache/1f91413f9d/rank_0_0/backbone for vLLM's torch.compile (EngineCore pid=332027) INFO 2026-09-22T04:10:32Z [backends.py:1155] Dynamo bytecode transform time: 18.51 s (EngineCore pid=332027) INFO 2026-09-22T04:11:06Z [backends.py:393] Compiling a graph for compile range (1, 8192) takes 31.91 s (EngineCore pid=332027) INFO 2026-09-22T04:11:16Z [backends.py:920] collected artifacts: 65 entries, 21 artifacts, 23738966 bytes total (EngineCore pid=332027) INFO 2026-09-22T04:11:16Z [decorators.py:719] saved AOT compiled function to /workshop/.cache/vllm/torch_compile_cache/torch_aot_compile/68c5a6dc0f2c201d2b474cd87ca1e2da1096f91157ef233b9354c637956adf0c/rank_0_0/model (EngineCore pid=332027) INFO 2026-09-22T04:11:16Z [monitor.py:53] torch.compile took 62.21 s in total (EngineCore pid=332027) /workshop/bench-vllm-venv/lib/python3.12/site-packages/triton/language/core.py:2284: UserWarning: tl.make_block_ptr is deprecated. Use TensorDescriptor or tl.make_tensor_descriptor instead. (EngineCore pid=332027) warn("tl.make_block_ptr is deprecated. Use TensorDescriptor or tl.make_tensor_descriptor instead.") (EngineCore pid=332027) INFO 2026-09-22T04:12:27Z [monitor.py:81] Initial profiling/warmup run took 70.37 s (EngineCore pid=332027) Capturing CUDA graphs (PIECEWISE): 0%| | 0/2 [00:00