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
- Add validation to reject non-text content in system messages
- Move the Python kernel abstraction package (selectors + interfaces) under `vllm/model_executor` so unquantized linear kernels don’t need to be referenced from a quantization-specific directory.
- [Bug]: vLLM crashes when trying to load Devstral-2-123B-Instruct-2512 directly from S3
- [Usage]: Unable to load Mistral-Small-3.2-24B-Instruct-2506-FP8 due to "Value error, Found unknown quantization", but the same configs worked for vllm v0.11.0
- [Bug]: vLLM-compile should not execute the decoder forward pass during compilation
- [Bug]: required numpy version mismatch between modules
- fix: optimize cold start compilation by triggering torch.compile with minimal batch size
- [ROCm][CI] Fix serving tokens test failures
- [Bug]: pd disaggregation on the same host with nixl connector can not use nvlink to transfer kv cache
- [Bug]: Qwen3-1.7B apparently not respecting max-model-len (can't generate >2048 tokens)
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