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
- [Bug][FP8] ScaledMMLinearKernel rejects valid non-contiguous batched activations
- [Feature]: Add support for Bailing MTP speculative decoding
- 💥 RTX 5090 + WSL2: V1 Engine hangs at startup — EngineCore spawns but never connects via ZMQ, ALL models fail (v0.21-0.22), raw spawn+Pytorch works fine
- CUDA device-side assert with nvidia/Qwen3.6-35B-A3B-NVFP4 + MTP on nightly f91fb2f
- [Installation]: ROCm install silently falls back to CUDA abi3 wheel on Python < 3.12 (no ROCm abi3 / cp311 / cp313 wheels)
- [Bug]: thinking_token_budget forces reasoning_end tokens into the middle of tool-call arguments — ThinkingBudgetStateHolder doesn't treat <tool_call> as implicit reasoning end (Qwen3.5+)
- [Test][Quantization] Restrict test_machete_mm gate to Hopper family
- [Spec][PP] Support MTP speculative decoding under pipeline parallelism (PP>1)
- [CI] Add opt-in statistically-calibrated lm-eval accuracy gate (Wilson lower bound)
- fix(kv_cache): domain-tag LoRA and cache_salt prefix-cache keys to prevent collision (#44701)
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- Python not yet supported