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] Preserve empty tensor metadata in packed IPC
- [Bugfix] Reject dynamic speculative decoding with ngram_gpu
- [Perf][MoE] Batch per-expert token count GPU sync into single transfer
- [Bugfix][Frontend] Honor default penalties in transcription and translation requests
- [Bugfix][Spec Decode] Apply min_tokens at the V1 bonus-token position
- [Perf][Distributed] Skip movedim+reshape for dim=0 in CudaCommunicator reduce_scatter
- [Perf][Distributed] Skip movedim+reshape for dim=0 in DeviceCommunicatorBase all_gather
- [Perf][Distributed] Skip movedim+reshape for dim=0 in DeviceCommunicatorBase reduce_scatter
- [Bugfix][Frontend] Return all top_logprobs when Responses API requests top_logprobs=-1
- [Benchmark] Add reproducible request cancellation workloads
- Docs
- Python not yet supported