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]: Host memory is not reducing after the model is loaded into Intel XPU
- [Bugfix] Make Rust HF dataset endpoint configurable
- [Bugfix][LoRA] Make Punica shrink deterministic with split_k=1
- [RFC]: Per-layer online quantization configuration
- [Feature]: Expose startup status and health endpoint before model engine is ready
- [Core] Add --enable-nan-fault-tolerance for NaN detection and request abort
- [Usage]: Does Kimi-K2.5 support `thinking_token_budget`?
- [Core][Spec Decode] Fix KV cache allocation for sliding-window drafters and local-attention pool sizing
- [Bugfix][Spec Decode] Warn when Eagle3 aux layers fall back to a default
- [3/N][Feat][Perf] Add new warmup infrastructure for JITs. Add provider registry and orchestration for JIT warmup
- Docs
- Python not yet supported