vLLM 0.25.0 Major Release: Architecture Upgrades and Multi-Hardware Optimizations

vLLM has officially released version 0.25.0, marking a massive milestone update. This major iteration comprises 558 commits and involves 232 contributors, 64 of whom are new. The update not only adjusts the core execution architecture but also brings broad hardware adaptations and engineering deployment improvements.

Core Architecture and Execution Path

The most significant change at the model execution level is that Model Runner V2 officially becomes the default execution path for all dense models, while the legacy execution path is deprecated. This signifies a major iteration in vLLM's underlying scheduling and inference logic.

Multi-Hardware Performance Optimizations

vLLM 0.25.0 introduces meticulous performance tuning for different underlying hardwares. For the NVIDIA platform, FlashInfer's fused all-reduce is specifically tuned for GB300, and support for the Blackwell architecture is refined. In addition, targeted optimization measures for other hardware platforms, such as AMD, are included.

Serving and Distributed Deployment Improvements

On the engineering deployment and serving fronts, version 0.25.0 implements multiple underlying refactors. For distributed deployment, sequence parallelism no longer mandates DP (Data Parallelism), an improvement that boosts end-to-end throughput by approximately 1.9% to 5.0%. Furthermore, adjustments and upgrades to NCCL-related settings and frontend components have been made to provide more robust server-side support.

2026-07-12 ~ 2026-07-12 · 5 related posts

1 near-duplicate retellings: vllm_project