Axion 1.0: How ByteDance Built a Fully Open Agent Foundation Model with Just 18K Training Examples

Building capable AI agents has historically required elaborate training pipelines — mid-training phases, direct preference optimization, on-policy distillation, and mountains of proprietary data. Axion 1.0, released on November 2, 2026 by a team from ByteDance, Duke University, the University of Maryland, and the University at Buffalo, challenges that assumption. It achieves competitive performance on hard scientific reasoning and tool-use benchmarks using a three-stage recipe, 18,363 training trajectories, and roughly 1,000 GPU-hours for the 122B variant — and releases everything under Apache 2.0.

The Axion 1.0 paper and project page make the case that data quality and task construction matter more than pipeline complexity.…