Anthropic has launched Claude Sonnet 4.6, an update to the company’s hybrid reasoning model that brings improvements in coding consistency and instruction following, Anthropic said.

Introduced February 17, Claude Sonnet 4.6 is a full upgrade of the model’s skills across coding, computer use, long-context reasoning, agent planning, design, and knowledge work, according to Anthropic. the model also features a 1M token context window in beta.

With Claude Sonnet 4.6, improvements in consistency, instruction following, and other areas have made developers with early access prefer this release to its predecessor, Claude Sonnet 4.5, by a wide margin, according to Anthropic. Early Sonnet 4.6 users are seeing human-level capability in tasks such as navigating a complex spreadsheet or filling out a multi-step web form, before pulling it all together across multiple browser tabs, said Anthropic. Performance that previously would have required an Anthropic Opus-class model—including on real-world, economically viable office tasks—now is available with Sonnet 4.6. The model also shows a major improvement in computer use skills compared to prior Sonnet models, the company said.

Claude Sonnet 4.6 is available on all Claude plans, Claude Cowork, Claude Code, the Anthropic API, and all major cloud platforms. Developers can get started by using claude-sonnet-4-6 via the Claude API. The model still lags behind the most skilled humans at using computers, Anthropic said. But the rate of progress means that computer use is much more useful for a range of work tasks, and substantially more capable models are within reach, Anthropic said. On the Claude Developer Platform, Sonnet 4.6 supports adaptive thinking and extended thinking, as well as context compaction in beta. Context compaction automatically summarizes older context as conversations approach limits, increasing effective context length, according to the company.

Anthropic also announced updates to its API. Claude’s web search and fetch tools now automatically write and execute code to filter and process search results, keeping only relevant content in context, improving both response quality and token efficiency. Also, code execution, memory, programmatic tool calling, tool search, and tool use examples now are generally available.