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][Quantization] Register compressed-tensors block-FP8 weight scale as weight_scale_inv
- [Helm] Add optional ServiceMonitor with metric filtering
- [Bug]: Triton top-p keeps the whole row when most of the vocab has zero fp32 probability
- [Bugfix][Metrics] Initialize offload usage and dev operation gauges at startup
- [Bugfix][Core] Count only held blocks against the sliding window admission cap
- [Benchmark] Fix benchmark_marlin so it runs, and add a ragged-M sweep
- [Bugfix][Metrics] Correct KV cache eviction and idle-time reporting
- Fast start d2d stacked
- [Bugfix][Attention] Make TRITON_MLA prefill batch invariant under chunked prefill
- [Bug][KV Connector] MultiConnector on prefill silently disables the hybrid KV cache manager, so a NixlConnector decode rejects every transfer with an opaque "NIXL compatibility hash mismatch"
- Docs
- Python not yet supported