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
- [Mamba][Quantization] Add Stage 1 (CPU-only, reference) int8 quantization utilities for SSM state
- [RFC]: fp8_ds_mla KV cache on pre-SM89 (Ampere) GPUs via software-dequant TritonMLA decode
- [CI][Releases] Trigger `perf-eval` Through Release Pipeline
- [kimik3][ROCm][Perf] Fuse the MLA q/kv RMSNorm pair in the module forward
- [Tests] Centralize GSM8K eval definitions
- [Bugfix][NIXL] Fail closed on HMA receive errors
- [Bugfix] Support 0-dim tensors in packed weight transfer
- [Kimi-K3][DCP] Publish prefill KV directly in MLA layout
- [Bugfix] DeepSeek-V4: don't emit an empty `<think></think>` block for reasoningless turns
- [Bugfix] DeepSeek-V4: render request-level tools after the system prompt
- Docs
- Python not yet supported