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]: Qwen3.5 (hybrid GDN) models cannot run dflash speculative decoding with pipeline parallelism (missing supports_aux_hidden_states_over_pp opt-in)
- [Bugfix] Use native memory fence for SHM broadcasts
- [Frontend] Support image inputs in the Decisions API
- docs(envs): fix stale VLLM_CPU_KVCACHE_SPACE default comment (follow-up to #60048)
- [Bug]: `--mamba-block-size` has no effect in any valid configuration after the removal of `mamba_cache_mode="all"`
- [Bug]: glm47 streaming parser silently swallows the rest of the stream (including the real tool call) after a stray `<tool_call>` token in prose
- [Feature] Add Winnow read strategy to the Decisions API
- [Bugfix][Parser] Keep a text-spelled reasoning marker as content in non-streaming parse
- [Bugfix][NIXL] Release unreachable prefill peers on failed heartbeat
- [Bugfix] Detect NVFP4 when a compressed-tensors format is a list
- Docs
- Python not yet supported