AI summarized from verified sources
Responses API with reasoning retention and compaction triples benchmark scores
API developers can efficiently boost model performance with Responses API and reasoning retention settings.
SOURCE CHECK
2 sources
Sources
Key Points
- 1Responses API enables retained reasoning
- 2Context compaction improves token efficiency
- 3Demonstrated 188% ARC-AGI-3 score improvement
OpenAI applied the Responses API with retained reasoning and context compaction to the ARC-AGI-3 benchmark. GPT-5.6 Sol's score rose 188% while using 6x fewer output tokens. The standard harness discarded reasoning after each move and dropped earlier actions as context filled, forcing restarts. Developers can now adopt these settings to improve real-world performance.
What happened
OpenAI switched the ARC-AGI-3 harness to the Responses API and enabled retained reasoning plus context compaction. This led to a major score improvement for GPT-5.6 Sol.
Impact
API users adopting these settings can expect better performance on long-running agent tasks and reduced token usage. It also highlights that benchmark results depend heavily on settings.