Executive Summary
- •Claude Sonnet 5.5 hit second place on the Artificial Analysis Intelligence Index using a max-effort configuration.
- •The model used ~193k output tokens per task, driving the average inference cost to $7.60.
- •Its agentic terminal performance is exceptional, but it sacrifices API cost efficiency to achieve it.
Community Sentiment
Key Developments & Data
Claude Sonnet 5.5 reached the #2 spot on the Intelligence Index with a max effort configuration, sitting just behind Opus 5.5.
At max effort, the model consumed ~193k output tokens per task, which is roughly 60% higher than Opus 5.5 and 7x that of GPT-6 Astra.
The massive token volume pushed the average cost to $7.60 per task, making it about 50% more expensive than the Sonnet 5 baseline.
Despite lagging in factual knowledge with a 54% accuracy score on AA-Omniscience, it dominated agentic workflows by hitting 64% on Terminal-Bench 4.0.
Anthropic kept the underlying API pricing flat at $2 per 1M input tokens and $10 per 1M output tokens.
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Zubiqo Strategic Assessment
Primary Impact
Enterprise developers and AI wrappers attempting to build cost-efficient autonomous agents for production environments.
Strategic Shift
Frontier AI labs are masking underlying architectural plateaus by using massive test-time compute and brute-force token generation to artificially inflate benchmark scores.
The Ripple Effect
API middleware providers will likely start implementing hard token caps on agentic loops to prevent developers from accidentally bankrupting themselves on $7-per-task inference costs.
This intelligence assessment is generated by Zubiqo's AI for informational purposes only.
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