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
- [KV Connector][2/N][NIXL] Pipeline-parallel support for PD-disaggregated serving with NIXL connector
- [Bugfix][Spec Decode] Fix vocab size validation for eagle/eagle3
- [Gemma4][Bugfix] Add LoRA support for Gemma4 MoE 26B model
- Add per-request speculative decode metrics
- [Bugfix][DSV4] MTP draft model: detect BF16 MTP on disk + skip quant_config
- [ROCm] Add per-call decode budget to sparse-MLA indexer
- v1/engine: emit prefix-cache KV-events at hash_block_size granularity for hybrid Mamba+Attention models
- [Perf][Frontend] Cache "<|0.00|>" anchor token id for ASR verbose segments
- [Usage]: embeddings API when task is generate
- Fix `previous_response_id` dropping tool calls from stored context
- Docs
- Python not yet supported