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
- Create `test_kimi_k2_thinking_nvfp4.py` for accuracy check
- [Bug]: Distributed inference hanging on a 2 node DGX spark cluster with Mistral 3.5 Medium 128B with TP=2
- [Usage]: vllm v1 not use `--no-enable-chunked-prefill` to disable chunked prefill.
- [RFC]: Zero-copy LoRA loading from tmpfs via mmap + cudaHostRegister
- [Bug]: EngineDeadError with Kimi-K2.6 model using vLLM 0.20.2
- [Bug]: SimpleCPUOffloadConnector: requests stuck in Waiting (Running=0) under sustained load / CPU offload
- [Bug]: Gemma-4 MoE Initialization Hang and Segfault
- [Bug]: Possible MooncakeConnector data inconsistency under PD load (`dst != src_post`) with `mooncake-transfer-engine-cuda13==0.3.10.post2`
- [Feature]: Enhance the security protection of ZMQ communication
- [Bugfix] Fix MooncakeConnectorWorker cleanup crash on partial init
- Docs
- Python not yet supported