⚡️A 9B embodied AI model beats GPT-6 Astra on 6 of 8 spatial grounding benchmarks. ACE Robotics' ACE-Brain-0.6 is fine-tuned from Qwen3.5-9B using ~1M spatial grounding samples with verifiable visual evidence. > 74.53 average across 7 public benchmarks, vs. 73.68 for Astra > 94.13 on ACE’s RobotGrounding benchmark, vs. 91.10 for Astra Beyond locating objects, the model can identify when a target is missing — a critical capability for robots that need to know when NOT to act. The data scaling results are just as interesting: > expanding training data from 260K to ~1M samples raised the average score from 69.3 to 74.5. > Simply adding more of the same data types improved scores by less than 1 point. New scenes, spatial relationships and diverse supervision drove the bigger gains.