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]:OOM during weight loading on H20 (141GB) in v0.13.0, but works in v0.12.0 (Qwen2.5-72B FP8)
- [Bug]: Stuck with a loop when tensor_parallel_size=2
- [Bug]: The base image used by rocm Docker is 7.0-complete, and rocm 7.0 does not support GFX1150.
- [Bug]: KV Cache grows continuously with just one chat completion request using meta-llama/Llama-3.2-1B on L40 GPU with Flash Attention and finally completed after 10 minutes
- [Bugfix] Fix ZMQ port bind race condition in shm_broadcast
- [Feature]: Running paddocr‑vl consumes an excessively large amount of memory.
- [Performance]: DeepSeek-V3.2 Performance Optimization Tracking
- [Performance]: The prefill phase in the disaggregated_serving_p2p_nccl_xpyd example exhibits poor performance
- [Bug]: Value of aborted requests of `vllm:request_success_total` metrics is always zero even if some requests were actually aborted
- [Bug]: MiniMax-M2.1 DP8EP Recipe Error on B200
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