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
- [ROCm] Use mfma_r4_w4 for long gfx942 FP8 MQA logits
- [Kernel] Scale elementwise kernel launches with the device, not just batch size
- [Bug] fix: LLM.__repr__ handles non-torch worker models (#61366)
- [RFC]: Re-evaluate per-iteration metrics as a foundation for orchestrator observability
- [Security] Contain Sentence Transformers module files
- [Frontend] Tokenize the /v1/systemone state once per decision and let big decisions take turns
- [ROCm][Perf][Qwen3.8] Mono decode follow-up: MXFP6 projections, attention front kernel, router through o_proj
- [RFC]: Simulated execution with pluggable timing models (building on #47922)
- [Spec Decode][Qwen3.5] RecoverSSM for Qwen3.5 / Qwen3-Next GDN
- [Bug]: return_sampling_mask=True has two independent request-level preconditions (temperature > 0 and top_k > 0) that are reported one at a time, and only after the engine is already running
- Docs
- Python not yet supported