Anthropic's Claude Opus 4.6 Puts Developers in Control of How Hard AI Thinks

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Anthropic has quietly shipped one of the most developer-friendly features in frontier AI to date. Claude Opus 4.6 and Claude Sonnet 4.6 now support effort controls — a simple API parameter that lets builders dictate exactly how much cognitive horsepower the model applies to a given task.

What Are Effort Controls?

The new effort parameter replaces the older budget_tokens approach with four human-readable levels:

LevelUse case
lowFast, cheap responses for simple lookups or routing
mediumBalanced reasoning for standard tasks
highDefault — deep chain-of-thought for complex problems
maxFull extended thinking, no cap on reasoning tokens

The model dynamically adjusts its internal chain-of-thought based on the selected level. Higher effort means more thorough reasoning but also higher latency and cost.

Why It’s a Big Deal

Previous extended thinking systems were all-or-nothing. You either paid for deep reasoning or you didn’t. Effort controls let developers match compute cost to task complexity — running low for thousands of cheap API calls while reserving max for the genuinely hard problems.

For agent frameworks and product builders, this is a meaningful efficiency lever.

What Else Came With Opus 4.6?

Beyond effort controls, the release ships:

Anthropic says developers should experiment with effort levels for their specific domains, as the optimal setting varies widely by task type.


Source: anthropic.com, infoq.com