Claude Opus 4.7

Claude Opus 4.7 has particular skills in areas such as software engineering, knowledge work, agentic tool use, and computer use. Claude Opus 4.7 was trained on a proprietary mix of publicly available information from the internet, public and private datasets, and synthetic data generated by other models. Throughout the training process Anthropic used several data cleaning and filtering methods, including deduplication and classification. Anthropic uses a general-purpose web crawler called ClaudeBot to obtain training data from public websites. This crawler follows industry-standard practices with respect to the “robots.txt” instructions included by website operators indicating whether they permit crawling of their site’s content. Anthropic does not access password-protected pages or those that require sign-in or CAPTCHA verification. After the pretraining process, Opus 4.7 underwent substantial post-training and fine-tuning, with the goal of making it an assistant whose behavior aligns with the values described in Claude’s constitution. Claude is multilingual and will typically respond in the same language as the user’s input. Output quality varies by language. The model outputs text only. The model was evaluated in a number of risk areas including Cyber, Loss of Control, CBRN, and Harmful Manipulation. This model supports a long context of up to 200K tokens (native context window) and demonstrates improved capabilities in tool use, computer use, and browser automation, such as those seen in Claude Code.