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
- [Model][Hardware][AMD] Fuse Two-pass MHA into single Causal MHA
- [Fusion] Apply manual activation+quant fusion to Muse-Glimmer and LFM2
- [Bugfix][LoRA] Confine FilesystemResolver to VLLM_LORA_RESOLVER_CACHE_DIR
- [Bugfix][Benchmark] Compute exact peak concurrency across Python and Rust
- [ROCm][Perf] Fuse the MXFP4 activation quant into AITER AR+RMSNorm
- [Bugfix][Frontend] Preserve Whisper text without timestamp tokens
- \[Quantization\] Add support for modelopt IQ2\_XS, IQ2\_XXS, and Q8\_0 checkpoints via b12x
- [Feature] Enable triton autotuning for config reliant kernels
- [Bugfix][Attention] Keep FlashInfer's plan() staging buffer pageable
- [Feature]: Route FlashInfer sparse-MLA decode autotune through the PP-aware tuning group and cache
- Docs
- Python not yet supported