Optimized Harness Achieves SoTA on ARC-AGI-3, Questioning Benchmark Validity
Angaisb_ · x · 2026-07-30
A developer pointed out that ARC-AGI-3 is not representative of actual model capability, as it is easily solvable through better testing harnesses.
For instance, achieving SoTA (State of the Art) on ARC-AGI-3 with GPT-5.6 Sol only required two setting changes: allowing the model to reason across multiple context windows and utilizing a canonical compaction implementation. This further proves that optimizing the testing toolchain significantly impacts LLM benchmark scores.
Related event: Optimized Memory Settings Triple GPT-5.6's Score on ARC-AGI-3(27 posts)→
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