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
- [Bugfix][KV Connector][NIXL] Support heterogeneous P/D TP for mixed MLA models
- [Bugfix] Reserve construction-time scratch across workspace slots
- [ROCm] Default AITER on for CDNA3+ when the package is installed
- Fix shutdown order: drain engines before stopping API servers with --api-server-count > 1
- [CPU][Bugfix] Respect expert map in unquantized MoE
- [Quantization][INC][XPU] Add online NVFP4 to AutoRound MXFP4 conversion
- [Performance]: Waiting requests re-walk their whole prefix-cache hit on every scheduling step
- [Bug]: enable_tower_connector_lora: get_mm_lora_token_counts() under-sizes punica wrappers in 8 models (startup/runtime token_lora_mapping asserts)
- [Bugfix] LLM.__repr__ crashes on non-torch worker models
- [Feat][Quantization] Online linear NVFP4 to MXFP4
- Docs
- Python not yet supported