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
- [Feature] Gigachat 3.5 support
- [ROCm][Perf] Add Qwen3 AITER fused QKV/RoPE KV-cache path
- [Feature] Add VidCom2 video token pruning
- [Bug]: torch.xpu.device_count() returns 0 despite zeDriverGet() returning 1 — regression in XPU device detection
- [Bugfix] Add per-type field validation to AnthropicContentBlock
- [Feature][Whisper] Native word-level timestamps (cross-attention + DTW)
- [Bugfix][DeepSeek V4] Avoid SM100 FlashMLA cache shape mismatch
- [Bugfix][MoE] Handle older FlashInfer FP8 MoE signatures
- [Bug]: Realtime STT (Voxtral realtime): self-sustained blank-token rut mutes live transcription for minutes over real speech
- [Bugfix][Spec Decode] Trim token_ids/logprobs left past a stop string under speculative decoding
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- Python not yet supported