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
- [Bug][DSA] Complete sparse top-k output after DeepSelect detects a NaN
- [Bug]: GLM-5.x sparse indexer: the replicated key norm is autotuned per rank, so TP ranks can select different candidates and greedy completions change from launch to launch
- [Bug]: MFU/MBU counts speculative-decoding steps as prefill (`is_prefill = num_tokens > 1`)
- [Frontend][Spec Decode] Populate metrics.speculative_decoding on /v1/responses
- [Test][Hybrid] Add TP2 Mamba2 prefix-cache hit regression
- [Bug][ROCm]: Qwen3.8-Flash-Next-FP8 cannot load on ROCm, the AMD Qwen4ExpNGramEmbedding has no FP8 weight_scale
- [Perf][Attention] Reuse KV loads across DiffKV prefill query positions
- [Bugfix][Spec Decode] Defer disposable DeepseekV32 MTP head for modelopt nvfp4
- [Perf] DiffusionGemma: skip the self-conditioning matmul on a read's last step
- docs(vllm): fix typos and duplicate word in comments and warning logs
- Docs
- Python not yet supported