vllm
https://github.com/vllm-project/vllm
Python
A high-throughput and memory-efficient inference and serving engine for LLMs
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Help out
- Issues
- Revert "[BugFix] Correct max memory usage for multiple KV-cache groups" (#36030)
- feat: add IBM POWER8 (ppc64le) CPU backend support
- add integration of xqa and fmha through flashinfer
- [ci] Use fresh cache directory for compile only per test case.
- [Bugfix] Add early detection for CUDA < 13.0 on sm_103+ GPUs (GB300)
- [Model] Support Qwen3 as MiDashengLM text backbone
- [Feature]: Allow user selection of structured output (xgrammar) backend for bitmask application
- [misc] enhance code robustness
- [Bug]: vllm bench: "Peak output token throughput" is "less than Output token throughput"
- [Bugfix] Fix SamplingParams bad_words tokenizer conversion for space-prefixed tokens
- Docs
- Python not yet supported