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
- feat(benchmarks): add TTFT and TPOT statistics to throughput benchmark
- Fix Qwen 3.5 tool calling problem
- feat(kv-offload): Strategy B — AdaptiveOffloadingPolicy + non-blocking loads
- [Spec Decode] Finite state machine speculative decoding
- [Bug]: Value error, Model architectures ['Qwen3_5MoeForConditionalGeneration'] are not supported for now
- [Perf] Optimize Sampler Redundant Copy for Model Runner v2, 1.8% Throughput Improvement
- [Feature]: Implement silu_mul_fp8_quant_packed for deepgemm for sm100 families
- [Performance]: curious new kernels from vllm 0.11.1
- [MIX] More accurate processing of quantization of `mlp.gate`
- [Feature]: Integrate RadixMLP into vLLM
- Docs
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