vllm
https://github.com/vllm-project/vllm
Python
A high-throughput and memory-efficient inference and serving engine for LLMs
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- Issues
- Add vllm:kv_offload_cpu_total_blocks capacity metric
- [cleanup] Add missing Exception handlers in Responses API serving paths
- [Bug]: ExampleHiddenStatesConnector full gather causes long-context OOM
- [MoE][Kernel] Add optional HPC BF16xFP32 router GEMM
- fix(sampler): fall back to native sampling when flashinfer is absent
- [2/N][Feat][Perf] Add new warmup infrastructure for JITs. Add predicate filtering for JIT warmup, and migrate Inkling FA4
- [Bug]: [Parser] kimi_k2 streaming tool-call args skip schema type coercion applied in non-streaming (silent type mismatch)
- [Bug]: [Performance] AsyncLLM `add_request` runs multimodal `process_inputs` (HF processor) synchronously on the event-loop thread, serializing per-request image preprocessing and starving the GPU under concurrent multi-image requests
- [Bugfix][Parser] kimi_k2: route streaming through arg_converter so schema type coercion applies
- [Bug]: logprob_token_ids: [] silently bypasses validation and is discarded, on both Chat Completions and Completions
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- Python not yet supported