AI News Digest — July 29, 2026 — MCP App Store

Yesterday was dominated by a significant breakthrough in model reasoning efficiency from OpenAI. The focus was on the ARC-AGI-3 benchmark, where strategic API adjustments led to a massive performance leap, suggesting that the gap between raw model capacity and actual benchmark performance often lies in how reasoning and compaction are configured.

Today's stories:

**How enabling two settings tripled our scores on the ARC-AGI-3 benchmark (OpenAI News) — OpenAI shows that fine-tuning reasoning and compaction settings can triple GPT-5.6's score on complex AGI benchmarks, emphasizing the importance of inference-time optimization.

How enabling two settings tripled our scores on the ARC-AGI-3 benchmark

OpenAI demonstrates how specific API settings for reasoning and compaction tripled GPT-5.6 performance on the ARC-AGI-3 benchmark. This highlights a critical optimization path for improving model efficiency and reasoning capabilities in complex problem-solving tasks.

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AI News — July 29, 2026

How enabling two settings tripled our scores on the ARC-AGI-3 benchmark

AI News — July 29, 2026

How enabling two settings tripled our scores on the ARC-AGI-3 benchmark