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]: tests/lora/test_gptoss_tp.py::test_gpt_oss_lora_tp2[True-False] fails in eager mode
- [vLLM IR] Port SiluAndMul
- [vLLM IR] Convert activations to `PluggableLayer`
- [CI] Automate Docker Hub release image publishing
- [Feature]: [parity with CUDA] PD disagg recipes on vllm
- [Bug]: v0.19.1 CUDA illegal memory access with --kv-cache-dtype fp8 + EP + EAGLE3 under concurrent load (Kimi-K2.5) - distinct from #40259
- [BUG] Port-allocation race between ApiServer processes in hybrid-LB mode (ZMQError: Address already in use)
- [Bug]: Per-attention-head quantization is currently available only with the Flash Attention backend and requires the calibration pathway provided by llm-compressor.
- [RFC]: Convert Triton kernels from raw pointers to block pointers
- [Bug]: Streaming output incorrectly mapped to `reasoning` field instead of `content` when `enable_thinking=False`
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