claude-opus-4-20250514-thinking

Basic Information

Claude Opus 4 is the flagship AI model in Anthropic’s Claude 4 series, released simultaneously on May 22, 2025. Built on Anthropic’s self-developed next-generation core technology architecture, the model’s API ID is claude-opus-4-20250514. It represents Anthropic’s pinnacle achievement in breakthroughs in high-end AI performance and adaptation to complex scenarios. Officially positioned as a “versatile flagship model for enterprise-level complex tasks,” it can be accessed by general users through the paid professional version on the Claude.ai web platform, as well as on iOS and Android apps. Developers can commercially integrate it via the Claude Developer Platform, Amazon Bedrock, and Google Cloud’s Vertex AI. The API interface supports smooth migration and compatibility with previous models. The official knowledge cutoff date is January 2025, and the training data cutoff date is April 2025, ensuring the model has up-to-date knowledge reserves.

Core Features

Flagship-Level Programming Capabilities: Tackling Complex Projects Across the Entire Workflow

Labeled by the official as the “preferred model for complex software development and system refactoring,” Claude Opus 4 excels in the SWE-bench Verified benchmark—a test that measures real-world software engineering capabilities. With a single-model configuration, it achieves an accuracy rate of 73.5%. After enabling Anthropic’s proprietary “parallel inference acceleration” technology, its accuracy further improves to 79.8%, placing it among the top-tier flagship models of its time. Official test data shows that the model can work autonomously for over 25 consecutive hours, generating approximately 9,800 lines of high-quality code in one go. It covers core tasks across the entire workflow, including large-scale project architecture design, cross-language code migration, deep debugging of complex bugs, and legacy system refactoring. It demonstrates exceptional adaptability especially in multi-file collaborative development and microservices architecture setup scenarios, fully meeting enterprise-level software development needs.

Advantages in Building Complex Agents: Core Engine for Enterprise-Level Intelligent Agents

The model is officially defined as the “core engine for building enterprise-level complex agents,” featuring industry-leading capabilities in plan coordination, multi-level memory management, and distributed sub-agent scheduling. Paired with Anthropic’s open Claude Agent Pro SDK, developers can quickly build sophisticated AI agent systems that support fine-grained permission control, dynamic task decomposition, and priority scheduling. The built-in agent state rollback feature enables precise control over task workflows. Official examples show that a financial risk-control agent built on this model can collaboratively execute over 1,000 sub-tasks, improving development efficiency by 60% compared to previous models, significantly lowering the technical barrier for deploying high-end intelligent agents. It is well-suited for enterprise-level agent-building scenarios such as financial risk control and smart manufacturing scheduling.

High-Efficiency Computer Operation Capabilities: Full-Process Automation at the Operating System Level

In the OSWorld real-computer task test, Claude Opus 4 leads comparable flagship models with a score of 58.7%, representing a performance improvement of over 40% compared to the previous Opus 3’s 41.9%. Official verification confirms that it can autonomously complete full-process tasks at the operating system level, including deep browser navigation, complex spreadsheet data modeling, batch processing of multiple file formats, database queries, and data entry. It seamlessly integrates with enterprise-level professional software such as SAP and Salesforce, directly calling local compilation environments for programming languages like Python and Java to execute complex scripts. It adapts to large-scale enterprise automation scenarios in office work, operations monitoring, and data processing.

Outstanding Reasoning and Knowledge Processing Capabilities: Deep Empowerment in Specialized Fields

The model performs exceptionally well in specialized domain reasoning tests, ranking among the industry leaders in key metrics: It scores 81.2% on the GPQA Diamond graduate-level reasoning test, 12 percentage points higher than the average of similar models; it earns 12 points (out of 15) in the AIME 2025 math competition, reaching an excellent level; and it achieves an accuracy rate of 88.6% in multilingual question answering (MMMLU), covering knowledge query needs across more than 100 specialized fields. Official industry test data shows that in specialized scenarios such as financial derivatives pricing analysis, legal compliance review, biomedical target screening, and cutting-edge STEM research, its logical reasoning and knowledge application accuracy improves by 35% compared to previous models, making it a core auxiliary tool for empowering business processes in specialized fields.

Multi-Modal and Parameter Advantages: Ultra-Large-Scale Task Adaptation

The model fully supports multi-format inputs—including text, images, tables, and PDF documents—and boasts comprehensive processing capabilities for over 200 languages, with small-language translation accuracy improved by 28% compared to the previous generation. Its maximum single-output capacity is 32K tokens, and the standard context window is 200K tokens. Through official application, the beta version can unlock a super-large context window of 1M tokens, enabling it to handle ultra-large-scale tasks such as entire books, large codebases (100,000 lines), and multi-volume academic papers in one go, meeting demands for generating long-form academic monographs, integrating multiple documents across domains into comprehensive reviews, and building enterprise-level knowledge bases.

Technical Highlights

Developer Tool Upgrade: Full-Process Adaptation for Enterprise Development

Equipped with the Claude Code v2 professional development suite, it adds “task breakpoint resumption” and “version iteration management” features, supporting progress saving, historical version rollback, and incremental updates for complex development tasks, thus avoiding loss of progress due to system interruptions or requirement changes. It provides native VS Code and JetBrains IDE extensions, as well as enterprise-level terminal interfaces, allowing direct code execution, project directory structure creation, and automated test case generation within conversational contexts. The built-in code quality detection tool outputs compliance reports in real time, greatly simplifying enterprise-level development processes. Official data shows that it can improve development efficiency by over 45%.

Advanced Security Framework: Enterprise-Level Security Compliance Assurance

Adopting Anthropic’s latest enhanced AI Safety Level 3 (ASL-3) release framework, it incorporates a triple-high-precision classifier filter that proactively identifies and blocks high-risk content such as chemical, biological, radioactive, and cyber attacks, achieving a blocking accuracy rate of 99.2%. Its resistance to prompt injection attacks is 15 times stronger than the previous generation, with a false-positive rate reduced to below 0.03%. It introduces a dynamic security assessment mechanism for the first time, automatically adjusting security policies according to different industry scenarios. It also features explainable AI technology, generating security audit reports on reasoning processes to meet compliance requirements in highly regulated industries such as finance and healthcare.

Cost and Deployment Optimization: Balancing Cost and Performance for Enterprises

The model supports flexible deployment across public clouds, private clouds, and hybrid clouds, adapting to enterprises’ varying security-level deployment needs. Official pricing is $8 per million input tokens and $40 per million output tokens. For enterprise users, a “tiered pricing” strategy is introduced: monthly usage exceeding 10 million tokens qualifies for a 30% discount. An innovative “intelligent prompt cache” feature is launched, which can save up to 85% of costs for repeatedly called fixed instructions and knowledge-base content, reducing costs by an average of 45% in batch-processing scenarios. This achieves an optimal balance between cost and efficiency based on flagship-level performance.

Market Impact

The launch of Claude Opus 4 is seen by the industry as a major milestone in the field of enterprise-level AI applications. Its three-dimensional core advantages—“flagship programming capabilities + complex agent engine + system-level operational capabilities”—mark the entry of AI into a mature stage of application in high-end production scenarios. With leading performances in specialized tests such as SWE-bench Verified 79.8%, OSWorld 58.7%, and GPQA Diamond 81.2%, it has become the preferred model for core scenarios including large-scale enterprise software development, high-end agent construction, financial risk control, and biopharmaceutical R&D. Since its launch, it has rapidly gained commercial partnerships with globally renowned companies such as Goldman Sachs, Microsoft, and Pfizer, particularly favored by industries with extremely high demands for performance, security, and stability, including finance, high-end manufacturing, and biopharmaceuticals. It is expected to drive innovation and efficiency in the intelligent transformation of high-end industries.