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
- [Distributed] SymmMem fused allreduce+RMSNorm: portable Triton kernel
- [CI] Narrow models_basic.yaml source dependencies
- [CI] Narrow models_language.yaml source dependencies
- [Frontend] Add x-vllm-* response headers for per-request stats
- [Perf] Triton fast path for `swap_blocks_batch` on small uniform batches
- [CI] Narrow entrypoints.yaml source dependencies
- [Core][Model] Gemma4: Unified FA4 for all layers + FlashAttention mm_prefix support
- [Bug]: GDN attention `mamba_get_block_table_tensor` torch.gather index out of bounds when prefix caching + num_speculative_tokens>=10 (DFlash, DGX Spark sm_121a, Qwen3.6 hybrid)
- [Bug]: SimpleCPUOffloadConnector + Hybrid KV Cache Manager: GPU block pool exhaustion (popleft_n assert) on second long-context request
- [New Model]: Add DebertaV2ForSequenceClassification (DeBERTa-v2/v3 cross-encoder / reranker)
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