Qwen releases Qwen-Drive-1.0, an open-weights vision-language model for autonomous driving
Qwen/Alibaba
The Qwen team open-sourced Qwen-Drive-1.0-4B under Apache-2.0: a frozen Qwen3.5-4B VLM with an attached BEV perception head (3D detection, occupancy, map segmentation) and a flow-matching planning expert with SFT and RL checkpoints. It posts NAVSIM PDMS 90.7 (91.4 best-of-6), WOD-E2E RFS 8.45 and best-in-table driving-VQA scores while barely degrading general VLM ability (MMMU 72.7). Weights appeared on HuggingFace in late August with the arXiv paper on August 31; mainstream coverage followed on September 7.
Why it matters
First open-weights general VLM from a major Chinese lab aimed end-to-end at driving (perception + planning), and one of the first attempts to keep general multimodal skills intact in a driving-specialized model — a template other AV teams can build on for free.
Importance: 3/5
Notable open-weights release: first driving-specialized VLM from a major Chinese lab, full weights and paper