Claude Opus 4.7 - Anthropic's latest flagship large model

What is Claude Opus 4.7?

Claude Opus 4.7 is Anthropic's latest flagship large-scale model, a direct upgrade from Claude Opus 4.6. The model excels in advanced software engineering tasks, achieving a SWE-bench Pro score of 64.3% and supporting a visual resolution of 2,576 pixels (approximately 3.75 megapixels). It also features self-verification and long-term autonomous execution capabilities. The model is now fully available across the entire Claude product line, API, and major cloud platforms such as Amazon Bedrock.

Main features of Claude Opus 4.7

• High-difficulty programmingIt scored 64.3% in the SWE-bench Pro test, demonstrating its ability to autonomously handle complex and time-consuming software development tasks and self-verify results.
• Ultra-high resolution visionIt supports image input with a long side of 2,576 pixels (approximately 3.75 million pixels), which is more than 3 times that of the previous generation model.
• Self-correction mechanismBefore reporting the final results, proactively check for logical errors, correct them internally, and then output them to reduce human intervention.
• Long-range task executionIt can run complex, multi-step workflows continuously for hours, maintaining stability and consistency.
• Multimodal understandingPrecisely interpret dense screenshots, complex technical charts, chemical structures, and pixel-level visual details.
• Smart tool callSupports extended toolchains such as MCP-Atlas, reducing tool call error rate by approximately 1/3.
• File system memoryRemember key notes across multiple sessions and long tasks, reducing repetitive context input.
• Added effort levelNew xhigh Gear (located in) high and max (between), Claude Code uses this level by default.
• Task BudgetsSupports setting token budgets for long tasks, allowing the model to allocate resources autonomously.
• Ultrareview commandClaude Code now features a new independent review session for in-depth checks of code changes and potential issues.

How to use Claude Opus 4.7

• Platform Access:
  • Claude Website/AppSimply switch to Opus 4.7 in the model selector to use it.
  • API callsModel ID is claude-opus-4-7It can be invoked via the Anthropic API, Amazon Bedrock, Google Cloud Vertex AI, or Microsoft Foundry.
  • Claude CodeThe effort level has been increased by default. xhigh,enter /ultrareview Deep code review can be initiated.
• API Key Parameter Settings:
  • effort gear:pass effort The parameter controls the response size; the option is... low / medium / high / xhigh / maxFor programming and agentic scenarios, it is recommended to use... high or xhigh Getting started.
  • task budgets(Public Beta): Set a long-task token budget to allow the model to allocate resources autonomously. This can be used in conjunction with the effort parameter for more precise control.
  • thinking parametersDeprecated thinking: {type: "enabled", budget_tokens: N}, changed to use thinking: {type: "adaptive"} Cooperate effort parameter.
• High-resolution visionUpload the original image directly with a long side not exceeding 2,576 pixels. No manual compression is required; the model will automatically process high-resolution input.
• Claude Code specific instructions:
  • enter /ultrareview Initiate an independent review session to conduct an in-depth inspection of code changes (Pro and Max users can enjoy up to 3 free reviews per month).
  • Auto mode has been made available to Max users. --dangerously-skip-permissions Provides an intermediate security option between the default mode and the default mode.

Key information and usage requirements for Claude Opus 4.7

• Model localizationOpus 4.6 is a direct upgrade and Anthropic's latest flagship model, now fully available across the entire Claude product line, API, Amazon Bedrock, Google Cloud Vertex AI, and Microsoft Foundry.
• Core upgradeSignificantly improved ability to perform high-difficulty software engineering tasks (64.3% improvement in SWE-bench Pro), visual resolution supports a long side of 2,576 pixels (approximately 3.75 million pixels, more than 3 times that of the previous generation), and has self-verification and long-term autonomous execution capabilities.
• Pricing strategyMaintaining the Opus 4.6 price, input $5/million tokens, output $25/million tokens, model ID is claude-opus-4-7.
• New gear:exist high and max New additions between xhigh The effort level is the default setting for Claude Code.
• Tokenizer changesThe new tokenizer generates approximately 1.0–1.35 times more tokens for the same text than the old version, requiring a higher token budget.

Claude Opus 4.7's core advantages

• Breakthrough in high-difficulty programmingIt scored 64.3% in the SWE-bench Pro test, an improvement of 11 percentage points from 4.6, demonstrating its ability to handle the most complex software engineering tasks autonomously.
• Self-verification mechanismProactively checking for logical errors and correcting them internally before reporting results significantly reduces the frequency of human intervention and improves the reliability of long tasks.
• Leap in visual perceptionIt supports high-resolution images with a long side of 2,576 pixels (approximately 3.75 million pixels), and the visual perception benchmark jumps from 54.5% to 98.5%.
• Long-term task stabilityIt can run complex, multi-step workflows continuously for hours without abandoning them due to midway difficulties, maintaining consistent execution.
• Strict adherence to instructionsThe accuracy of literal execution of instructions has been greatly improved, reducing ambiguity and ensuring that the instructions are executed precisely as intended by the user.
• Tool call efficiencyThe error rate of tool calls has been reduced by about one-third, and the efficiency of token usage has been significantly optimized in multi-step agentic scenarios.

Project address for Claude Opus 4.7

• Project official websitehttps://www.anthropic.com/news/claude-opus-4-7

Comparison of Claude Opus 4.7 with similar competing products

Application scenarios of Claude Opus 4.7

• High-difficulty software developmentIt supports handling complex software engineering tasks, such as large-scale code refactoring and complex algorithm implementation. It can run autonomously for several hours and self-verify the results before reporting. In GitHub tests, the task resolution rate has been improved by 13%.
• High-resolution visual analysisThe model can interpret dense UI screenshots, technical charts, chemical structures, and pixel-level visual details, making it suitable for computer vision proxies, automated penetration testing, and life science patent workflows.
• Long-range autonomous workflowIt can automatically perform complex, multi-step tasks across multiple sessions, such as in-depth data analysis and research report generation, maintaining consistency and coherence over long periods of operation and reducing human intervention.
• Financial and Business AnalysisThe model is capable of rigorous financial modeling, investment analysis, and professional presentation generation, scoring 64.4% in the Finance Agent v1.1 benchmark test, and can produce rigorous analytical models and high-quality business deliverables.