OpenAI Reveals Compaction Boosts GPT-5.6 ARC-AGI-3 Score to 38%
ilanbigio · x · 2026-07-30
An OpenAI engineer noted that model evals rarely measure models in isolation. When enabling context compaction and reasoning retention mechanisms, the model's performance on complex tasks improves significantly.
Core evaluation data:
- With these mechanisms enabled, GPT-5.6 Sol (max) saw its score on the ARC-AGI-3 benchmark jump from 13% to 38%.
- Achieved this while using 6x fewer tokens.
This indicates that effective context management and memory compression are critical for sustaining long-horizon reasoning capabilities.
Related event: Optimized Memory Settings Triple GPT-5.6's Score on ARC-AGI-3(27 posts)→
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