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] AITER v0.1.23 bump: gfx950 a16w4 MXFP4 MoE Gluon backend crashes (AttributeError get_scaled_upcast_fp4_scale_layout)
- [Bug]: Greedy output changes between restarts, also with VLLM_BATCH_INVARIANT=1: the q/k-norm + RoPE combo kernel picks its reduction config by timing
- [Bugfix][Core] Count the external claim's state block in MambaManager admission
- [Docs] Document NIXL KV connector metrics aggregation semantics
- [RFC] RL Weight Update Roadmap
- [Feature]: [RFC] Dynamic Latent-Trajectory Consensus Governor for Reasoning Models (DeepSeek-R1 / QwQ) to Free KV-Cache 4.5x Faster
- [Bug]: Intermittent Xid 31 MMU fault in pynccl all_reduce during CUDA graph
- [Bug]: MRotaryEmbedding + YaRN uses 4x original_max_position_embeddings for the YaRN correction range and cache size
- [Feature]: Allow LBNHC/NHD for ROCM_AITER_UNIFIED_ATTN where supported
- [Bugfix][Quantization] Name the layer when a MoE expert weight is unquantized
- Docs
- Python not yet supported