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]: Add request-level OTel span attribute for cached prefix-cache input tokens
- [Performance]: RMSNorm op in v0.20 IR layer prevent further pytorch/triton op fusion
- [Bug]: CUDA illegal instruction in Mamba2 mixed prefill/decode path
- [Bug]: OverflowError in mamba_utils.collect_mamba_copy_meta on XPU when device pointer ≥ 2^63 (hybrid models with align-mode prefix caching)
- [RFC]: Adaptive throughput/latency profile for RL rollout long-tail
- [Feature]: Support Dynamic Pruning for Speculative Decoding Draft Trees in EAGLE-3
- [Performance]: KV prefetching not spawned on time can cause unnecessary GPU idle
- [Bugfix] Use NVFP4 packed layout for SlidingWindowSpec.real_page_size_bytes
- Fix #30128
- Fix: merge default stop_token_ids with request stop_token_ids in to_sampling_params
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- Python not yet supported