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
- [RFC]: Back-pressure detection for KV cache offloading tiers
- [XPU] Gate FlashAttention-in-graph on oneAPI 2026.0+ runtime support
- [Bugfix][NIXL] Release a dead peer's NIXL state without waiting for TTL
- docs: clarify post-generation checks vs logits processors
- Support mm_processor_cache in the Transformers multimodal backend
- [RFC]: Shared Context Parallelism: peer-addressable GPU objects for PCP and DCP
- [Bug] should_custom_ar()'s size threshold makes all-reduce kernel selection batch-dependent, which is why custom all-reduce can't simply be re-enabled under VLLM_BATCH_INVARIANT
- [Bug]: Kimi-K3 (TP=8, prefix caching): recurring illegal-memory-access crashes under concurrent load
- fix(dp): avoid get_open_port() infinite loop when VLLM_PORT is DP-reserved
- [Bug]: NVFP4 KV writes V block scales in the SM100 trtllm-gen swizzle unconditionally, silently corrupting the SM120 FlashInfer XQA route
- Docs
- Python not yet supported