OpenAI reports that enabling just two API settings tripled its scores on the ARC-AGI-3 benchmark with GPT-5.6, a demonstration that inference-time configuration—not only model scale—can reshape performance on tough abstract-reasoning tests.
The gains came from two specific mechanisms: retaining reasoning across steps and enabling compaction. Together, these settings boosted both scores and efficiency, preserving the model's problem-solving process while optimizing computation.
The result points toward a future in which benchmark performance depends as much on how reasoning is orchestrated at deployment as on the underlying model architecture.
Editorial consensus: All three drafts agreed that two API settings—retaining reasoning and enabling compaction—tripled GPT-5.6's ARC-AGI-3 scores, with no substantive disagreement.
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