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
- [BugFix] Defer API-server port binding for the Rust front-end and Ray DP; retire defer_api_server_ports
- feat: add SSE keep-alive comments for idle streaming responses
- [Bug]: DeepSeek-V4 sparse-decode MLA kernel wedges in a spin loop with no timeout and no diagnostic (device-level capture on sm_103; surfaces 300 s later as an unrelated DeepGEMM assert)
- [Frontend] Support repetition_detection as a server-side default
- [Feature][Model] Support stable-window-aware KV reuse for Qwen3-ASR realtime
- [Bugfix][Quantization] Fix MXFP4 conversion for FlashInfer CUTLASS
- [Model] Kimi-K3: all requests degenerate to a repeated token after long-context prefill (NaN logits; packed KDA prefill suspected)
- Extend FP8 asm MLA prefill to non-divisor small head counts
- DeepSeek-V4-Flash-0731: KV cache holds only 150K tokens in 7.7 GiB (56 bytes/token), max_model_len capped at ~121344 on H20 TP=2
- [MyPy][2/N] Fix mypy errors in small tests/ dirs
- Docs
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