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
- Apply current settings to Harmony continuations
- [V1] Add generic imperative KV-connector step lifecycle helpers
- [Bug]: deepseek-v4-pro-dspark --max-num-batched-tokens 16384 no use
- [Bug]: deepseek-v4-pro with --max-num-batched-tokens 16384 custom-all-reduce failed
- [ROCm][P/D] Fix MoRIIO READ prefix-cache block matching
- [Bug]: Qwen3.5-122B-A10B-FP8 serve crashes on nightly/0.25 (CUBLAS_STATUS_EXECUTION_FAILED at profile_run); no version serves FP8 hybrid GDN + DFlash together
- [RFC] Fail-Closed Graph Storage Contract for Weight Reload
- Update vendored LMCache connector for current IPCCacheServerKey API
- [Bugfix][CPU][RISC-V] Trust native RVV capability probe
- [RFC]: fp8 KV cache for the Ampere sparse-MLA path (TRITON_MLA_SPARSE) via software dequant
- Docs
- Python not yet supported