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Claude Opus 5.5 Intelligence, Performance and Price Analysis (Max)
Claude Opus 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) is amongst the leading models in intelligence, but somewhat expensive when comparing to other models of similar price. The model supports text and image input, outputs text, and has a 1M tokens context window.
Claude Opus 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) scores 58 on the Artificial Analysis Intelligence Index, placing it well above average among comparable models (median: 25). When evaluating the Intelligence Index, it generated 260M tokens, which is very verbose in comparison to the median of 88M.
Pricing for Claude Opus 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) is $4.00 per 1M input tokens (somewhat expensive, median: $2.00) and $20.00 per 1M output tokens (somewhat expensive, median: $10.00). In total, it cost $8708.20 to evaluate Claude Opus 5.5 (Adaptive Reasoning, Max Effort, Default Fallback) on the Intelligence Index.
This page shows the reasoning version of this model.
Metrics are compared against models of the same class:
Artificial Analysis Intelligence Index v4.3.2 includes: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
Artificial Analysis Intelligence Index v4.3.2 includes: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
Indicates whether the model weights are available. Models are labelled as 'Commercial Use Restricted' if commercial use is limited by conditions, and as 'Non-commercial' if the license prohibits commercial use.
Measures the performance of models on specific capabilities and industries
While model intelligence generally translates across use cases, specific evaluations may be more relevant for certain use cases.