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
- fix: Use global DP index for MooncakeConnector bootstrap registration
- [ROCm] Portable Triton paged-MQA-logits kernel + vectorized torch fallbacks for the DeepSeek-V4 sparse indexer
- [Performance] DP8 vs TP8 for single-KV-head MLA: 7.7x KV, 3.4x faster 1M TTFT at c=8 (DeepSeek-V4-Flash-0731, 8x B200, vLLM v0.25.0)
- [Performance] MiniMax-M3-NVFP4 on 8x B200, first numbers after the #48929 correctness fix: 1M real-prose envelope, EAGLE3 2.1-2.3x decode
- [Bugfix][Parser] Stream Inkling plain-text answers incrementally
- [Perf] Keep staged writes in NumPy chunks
- [Model Loader][Perf] Auto-prefetch VirtioFS checkpoints
- [Bugfix][Benchmark] Preserve SSE output across transport chunk boundaries
- [RFC]: Adopt otel genai semantic conventions for metrics
- [Bug]: VLLM_BATCH_INVARIANT=1 returns non-identical logprobs across repeats of a byte-identical concurrent workload at ~44 co-resident sequences
- Docs
- Python not yet supported