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
- [Kernel] Fuse logit softcapping into a single Triton kernel
- [Bug]: gemma4 31B MTP Avg Draft acceptance rate: 0.2%
- [Bugfix][Model] Fix DeepSeek V4 scale_fmt default for non-canonical quant configs
- [Bugfix] find_loaded_library: skip stub libraries and continue iterating
- [KV Offload] Expose SimpleCPU offload metrics
- [Doc] Add JarvisLabs deployment guide
- [Attention][MLA] Add Triton-fused TurboQuant decode backend
- [Feature]: Polymorphic buffer management for V1 worker (CPU/GPU staged tensors, lower hot-path overhead)
- [Bug]: Decode Context Parallelism (`--decode-context-parallel-size`) output drift and gibberish in v0.21.0 and latest nightly
- 📝 Integration Proposal: CAJAL — Scientific Paper Model Serving
- Docs
- Python not yet supported