ARC Prize 公布 Gemini 4 Argon 完整评测结果
ARC Prize 放出 Gemini 4 Argon 在 ARC-AGI 基准上的完整成绩，并附排行榜、复现仓库与测试政策链接。
@Google - Leaderboard: https://arcprize.org/leaderboard - Reproduce the public results: https://github.com/arcprize/arc-agi-benchmarking - Testing policy: https://arcprize.org/policy - Full Gemini 4 Argon results: https://arcprize.org/results/google-gemini-4-argon
Gemini 4 Argon from @Google on ARC-AGI (Verified): - ARC-AGI-3: 97.5%, $4.8K (provider adapter harness), 49.8%, $5.8K (standard harness) - ARC-AGI-2: 91.3%, $0.32/task - ARC-AGI-1: 98.5%, $0.16/task Google DeepMind is the second frontier AI lab to score above 95% on ARC-AGI-3.
@Google Argon's 97.5% score on ARC-AGI-3 is second only to GPT-6 Astra's 99.9% score. Like Astra, Argon used 62% fewer actions than the human baseline across the 25 ARC-AGI-3 public games. It matched or beat the speedrun record on 3 games and came within 10% on 6 others.
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
