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
- [Usage]: How to use vllm bench serve to bench remote deployed vllm models (can't bench when ep enabled!!!)
- [Usage]: Qwen3-32B on RTX PRO 6000 (55s First Token Delay and 15t/s)
- [Bug]: Inductor fails to fuse pointwise ops with sequence parallelism + async TP
- [RFC]: Coordinating vLLM and PyTorch Release Timelines. Starting with PyTorch Release 2.10
- [Bug]: `Eagle` spec decoding not working with Gemma2
- [RFC]: Fault-Tolerant Expert parallelism phase 2 (recovery)
- [Bug]:model response repeat same sentence and never stop on v0.11.x version, v0.10.2 is ok
- Update delta_text and model_output format to include newline
- [Bug]: CUDA error: an illegal memory access was encountered CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
- [Usage]: Error: Failed to initialize the TMA descriptor 700
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