ACE Robotics releases ACE-Brain-0.6, a 9B embodied model fine-tuned from Qwen3.5-9B on ~1M grounding samples, claiming to beat GPT-6 Astra on six of eight spatial-grounding benchmarks

Why it matters

【Key points】

Chinese robotics startup ACE Robotics (大晓机器人, founded by SenseTime co-founder Wang Xiaogang) released ACE-Brain-0.6 around midday on October 19, an embodied foundation model focused on visual grounding: turning an instruction like "put the fruit in the basket" into exact image locations — where the target is, where to place it, which part to grasp, or that the target isn't there. It is a 9B model fine-tuned from Qwen3.5-9B with the vision encoder frozen.

Company-reported results: it beats OpenAI's GPT-6 Astra on six of eight grounding benchmarks (e.g. Where2Place 76.55 vs 71.10, RoboSpatial 74.82 vs 69.55, RoboAfford 88.51 vs 84.94), averages 74.53 vs 73.68 on seven public benchmarks, and scores 94.13 vs 91.10 on its own real-robot RobotGrounding set (2,591 questions, 14 task types).

Training used ~1M samples (940k images, 2.7M QA pairs) from 30+ open robot datasets plus private egocentric data, auto-labelled with Grounding DINO and SAM 3. Scaling data from 260k to 1M lifted the seven-benchmark average from 69.3 to 74.5 (about +2.4 per doubling); adding more of the same data type gave under 1 point.

【Verifiable】

Wenhui Daily via Sina: https://finance.sina.com.cn/jjxw/2026-10-19/doc-inivtuer6188756.shtml

PingWest (full release): https://www.pingwest.com/w/318504

Previous ACE-Brain-0.5 on HF: https://huggingface.co/ACERobotics/ACE-Brain-0.5-8B

【Our read】

1. All numbers are self-reported and unreplicated; no 0.6 weights on Hugging Face yet (0.5 was released openly in July).

2. A 9B model edging a general flagship on narrow grounding tests shows verifiable labelled data matters more than scale for robot spatial perception; a 0.85-point average lead is not "better than Astra" overall.

3. The data-scaling curve and reliable "target absent" answers, which prevent wrong robot actions, are the parts to watch.