In addition to its strong performance on ARC-AGI-3 using the provider adapter harness (which preserves opaque reasoning and enables automatic compaction), Argon is also notable for its high scores using the standard harness (which enables the model to carry forward notes between turns).

However, we encountered API issues that prevented us from completing testing with the standard harness:

• Low reasoning: 49.8%, with runs completed on 42 of 55 games
• Medium reasoning: 46.3%, with runs completed on 46 of 55 games
• High reasoning: Runs completed on only 19 of 55 games, so we did not publish a score

Reported scores include all 55 games, retaining partial credit earned on incomplete runs.

We used the current introductory pricing of $2 input / $10 output per million tokens to calculate the costs.

Full results: https://arcprize.org/results/google-gemini-4-argon