Evaluation company Artificial Analysis published a comparison on X on 12 November in which it ran Anthropic’s current Claude models at every reasoning effort level. It set each setting’s score on its own Intelligence Index benchmark suite against the cost of one task. The company concluded that moving up a model tier buys more intelligence per dollar than raising a smaller model’s reasoning effort to the maximum.

Reasoning effort is an API setting, called effort. Anthropic’s guidance says it governs how much the model thinks, calls tools and checks its own work. On the Messages API the default is high on most models but medium on Opus 5.5 and Haiku 5.5. From cheapest to most expensive, Anthropic’s models are Haiku 5.5, Sonnet 5.5, Opus 5.5 and the frontier model Fable 5.2.

A larger model beat a smaller one at maximum effort

Artificial Analysis said the largest model sits on the efficiency frontier at almost every cost level, meaning no other setting scores more for the same price.

Opus 5.5 scored 57 at xhigh and Sonnet 5.5 scored 55 at max. Opus’s cost per task was 40 per cent lower, and it took about half as long as Sonnet. The chart in the post shows 15.9 and 32.6 minutes per task.

Fable 5.2 at high beat Opus 5.5’s max score, but the savings were smaller. The chart shows Fable scoring 3 points more at 10 per cent lower cost and taking 16.7 minutes per task against Opus’s 25.1. Fable 5.2 at low also beat Opus 5.5 at high.

The price list would not predict the result: Anthropic says each of Opus 5.5’s token prices is twice Sonnet 5.5’s. Anthropic’s guidance notes in general that a more capable model can complete a task with less work.

The rule does not hold in the cheapest tier

Artificial Analysis said every step up from Haiku 5.5 at max costs more. In the chart, Sonnet 5.5’s cheapest setting, low, scores lower than Haiku 5.5 at max yet still costs more.

The figures apply to Artificial Analysis’s own task set. Anthropic’s guidance says how much accuracy a lower reasoning effort costs depends on the task. In Anthropic’s own test on a subset of the SWE-bench Pro coding benchmark, Opus 5.5 at xhigh matched Fable 5.2 at high for a little over half the cost per solved task. For most agent tasks, the company recommends starting with Opus 5.5 at its default effort and comparing models on your own workload by what a finished task costs. If quality falls short, the guidance advises restoring the lowered reasoning effort or trying the next model tier at its default effort.