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
- [Feature]: It's user unfriendly to panic when there is not enough VRAM to serve at least one request with the max seq len
- [BugFix] Fix shared reference bug in parsers for n>=2 and streaming
- [Bug]: cuda graph takes too much memory for qwen 3.5
- [XPU] Fix spec-decode UTs under tests/v1/spec_decode
- [WIP] Prototype MM batcher interface
- [Bug]: VLLM_CPU_OMP_THREADS_BIND=nobind cannot be used with tp>1 on CPU backends
- [RFC]: Incremental MoE Expert Offloading — GPU Cache + Async Pipeline
- [Usage]: How to do offline inference on one rank in a distributed environment?
- [RFC]: Multi-tier KV offloading via the vLLM offloading connector
- [Feature]: PagedEviction: Structured Block-wise KV Cache Pruning for Efficient Large Language Model Inference
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