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]: Max token length incorrect when /nothink tag on Qwen3.5-4B
- [Bug]: The KV cache size log is wrong for Qwen3.5
- [Bug]: RoutedExpertsCapturer host buffer undersized for hybrid models with multiple KV cache groups
- [Bug]: ValueError: Gemma4ForConditionalGeneration does not support LoRA yet.
- [Feature]: Prefix caching completely ineffective for Mamba-hybrid models (Qwen3.5) when prompt < block_size (528 tokens)
- [BugFix] Correct OTEL span start time for Dynamo compilation
- [Bug]: Scheduling deadlock in _mamba_block_aligned_split with multiple large multimodal inputs on hybrid Mamba models
- [BugFix] Fix Gemma4 'layers.0.moe.experts.0.down_proj_packed' KeyError issue
- [Kernel][MoE] Add H200 tuned config for Gemma4 MoE on TP=8/4/2/1
- [Kernel] Add bf16 mm gemm flashinfer backend
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