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] DFlashProposer assumes a single KV-cache group; breaks with hybrid sliding+full-attention drafters
- [Bugfix] benchmark_moe: do not abort tuning when a candidate config fails Triton compilation
- [CI] Solidify speculative decoding E2E coverage
- [Bugfix][Spec Decode] Support hybrid-attention DFlash drafters spanning multiple KV cache groups
- [Bug]: With qwen3.5-35b-a3b, the performance is relatively poor both when using dflash and when not using it, but the accepted length of dflash is around 5–6.
- [PD] Emit inactive KV blocks for decode affinity
- [Bugfix][Model] Fix Qwen3.5 MTP for text-only checkpoints
- [Spec Decode][Perf] Optimize DSpark Markov head with addmm
- [Bugfix][Core] Fix invalid block handling for hybrid KV cache groups
- [Bugfix][CPU][RISC-V] Fix FP16 rounding and cross-compilation capability handling
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