Opus 5 looks far more cost-efficient than GPT-5.6 Sol on long-horizon agent tasks
daniel_mac8 · x · 2026-07-25
The post argues that critics misread the AA-Index cost-per-task chart when comparing Opus 5 to other models. Most AA-Index tasks are single-turn, so they do not capture the efficiency gains that appear on long-horizon agentic workloads.
The author points to ARC-AGI-3 as a better example: when a model can run for roughly 10,000 steps, they say Opus 5 becomes vastly more performant per unit cost than GPT-5.6 Sol.
Related event: Hyperagent Tests: Flagship Model Competition Shifts to Style and Cost(6 posts)→
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