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]: kimi-k2 gets wrong tool_call_id
- [Bug]: CUDA Graph Replay Skips KV Transfer Synchronization in Full Cache Hit Scenarios
- [Bug]: DSR1 fp4/fp8 MTP with spec num 3 has perf drop when enable async-scheduling
- [Bug]: single node 8 h20,ebo failed!
- [Bug]: First call to llama model takes too much time compared to subsequent ones
- [Feature]: could develop vllm java client sdk with langchain4j
- [RFC]: Add Balance Scheduling
- [Installation]: RM has detected an NVML/RM version mismatch
- [Bug]: memoryerror for transformers utils' parse_safetensors_file_metadata function when loading awq models since vllm 0.11.1
- [llama4_eagle] add lm_head attribute to model class
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