Anthropic Unveils Claude Opus 4.6: 1M Context, Agentic Coding, and Advanced Reasoning

San Francisco, CA – February 5, 2026 – Anthropic, a leader in AI safety and research, today announced the release of Claude Opus 4.6, its most sophisticated and capable model yet. This latest iteration significantly expands the model's capacity for long-context reasoning, introduces advanced agentic coding functionalities, and integrates novel adaptive reasoning controls, promising a new era for high-value knowledge work and complex AI-driven tasks.

Building upon the foundation laid by Claude Opus 4.5, the Opus 4.6 model represents a substantial leap forward, particularly in its ability to process and reason over vast amounts of information. A headline feature is its new 1 million token context window, a significant increase that enables the model to maintain coherence and understanding over much larger documents, codebases, and complex datasets. This expanded context is crucial for applications requiring deep comprehension and nuanced interaction with extensive information.

Revolutionizing Coding and Agentic Workflows

Anthropic highlights Opus 4.6's enhanced performance in agentic coding, a domain where AI models can autonomously plan, execute, and refine tasks. According to an announcement on Anthropic's news site, Opus 4.6 "plans more carefully, sustains agentic tasks for longer, can operate more reliably in larger codebases, and has better code review and debugging skills to catch its own mistakes." This makes it a powerful tool for software development, code refactoring, and complex debugging scenarios.

The model's capabilities extend beyond just coding. Opus 4.6 is designed to excel in a range of everyday work tasks, including financial analyses, in-depth research, and the creation and manipulation of documents, spreadsheets, and presentations. Within Anthropic's experimental Cowork environment, where Claude can multitask autonomously, Opus 4.6 is poised to significantly enhance user productivity by leveraging these integrated skills.

State-of-the-Art Performance and Safety

Anthropic reports that Claude Opus 4.6 achieves state-of-the-art performance on several key evaluations. It has secured the highest score on the agentic coding benchmark [Terminal-Bench 2.0](https://www.tbench.ai/news/announcement-2-0) and leads other frontier models on [Humanity's Last Exam](https://agi.safe.ai/), a rigorous multidisciplinary reasoning test. Furthermore, its performance on [GDPval-AA](https://artificialanalysis.ai/evaluations/gdpval-aa), an evaluation focused on economically valuable knowledge work in finance, legal, and other sectors, surpasses that of the industry's next-best models.

The development of Opus 4.6 also incorporates expanded safety tooling capabilities. Anthropic has a long-standing commitment to AI safety, with dedicated research teams focusing on alignment, interpretability, and societal impacts, as detailed on their research page. This focus ensures that as models become more capable, they also become more reliable and aligned with human values.

Broader Availability and Previous Iterations

Claude Opus 4.6 is now accessible on claude.ai, through the Claude API, and via major cloud providers under the identifier `claude-opus-4-6`. This release follows a series of advancements, including Claude Opus 4.1, which was released on August 5, 2025, and focused on improving agentic tasks and real-world coding performance. Prior to that, Claude Opus 4.5, announced on November 24, 2025, had already set new standards in coding, agentic capabilities, and enterprise workflows. The continuous development, as seen with the progression from Opus 4 to Opus 4.1 and now 4.6, underscores Anthropic's dedication to pushing the boundaries of AI capabilities.

This release signifies Anthropic's ongoing commitment to developing AI that is not only powerful but also reliable and beneficial for a wide range of applications, from cutting-edge research to everyday enterprise tasks.

Sources: Anthropic.com (News, Claude Opus pages), MarkTechPost.com