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]: Supporting Multi MTP layers in Speculative Decoding (EagleProposer)
- [Performance]: b200x8 deepseek-ai/DeepSeek-V3.2-Exp max perf
- [Usage]: how to pass param logits_processors in AsyncEngineArgs?
- [Bug]: Behavior change 0.11.2 vs 0.12 (and up)
- [Feature]: Sort blocks by block_id in FreeKVCacheBlockQueue.append_n to enable contiguous allocation
- [Misc] Remove redundant all reduce in qkv split for ViTs
- [Bug]: "No tokenizer file found in directory" is seen when serve model from local directory after upgrading vllm from 0.11.2 to 0.12
- [Bugfix] Apply RMSNorm weight correction for Gemma2 GGUF models
- [Bug]: DeepSeek on B300 reports `invalid numeric default value` error
- [RFC]: Why custom_mask is not exposed on FlashInfer to get more flexible use case?
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