The Claude Opus 4 API provides RESTful and gRPC endpoints that enable developers to seamlessly integrate Opus 4’s hybrid reasoning, 64K-token context management, and agentic tool-invocation capabilities into enterprise-grade AI workflows.
Basic Information & Features
Claude Opus 4 is positioned as Anthropic’s “most advanced model,” optimized for coding, reasoning, and agentic search. It introduces two distinct operational modes:
- Near-instant responses for latency-sensitive interactions.
- Extended thinking (beta) for deeper reasoning and tool integration, allowing the model to allocate more compute to logic and planning when needed.
The model supports a 7-hour memory span for sustained tasks, reducing “amnesia” effects common in long-form workflows. New features include thinking summaries, which surface concise reasoning chains rather than full, verbose internal logic, improving interpretability for developers. Opus 4 is 65% less prone to “shortcut” behaviors and exhibits stronger context retention when granted local data access.
Technical Architecture and Details
At its core, Claude Opus 4 leverages a transformer-based backbone augmented by a hybrid reasoning engine, designed to balance throughput with depth. Its architecture comprises:
Dual-Path Inference Engine
Shallow Path: A lightweight transformer optimized for sub-150 ms median latencies, handling straightforward queries with streamlined computation.
Deep Path: A computation-intensive network for extended thinking, enabling chain-of-thought reasoning and tool orchestration across thousands of tokens.
Tool and Plugin Integration
Native API Extensions: Direct interfaces for file systems, browsers, databases, and custom plugins, empowering Opus 4 to execute code, update documents, and interact with third-party services within a single prompt .
Memory and Context Management
Segmented Context Window: Supports a 200K-token native window, with memory compression enabling effective handling of up to 1 million tokens through indexing and prioritization algorithms .
Persistent Session Memory: Retains critical facts and user preferences across multi-turn interactions, improving continuity in long-running workflows.
Multimodal Processing Pipeline
Visual Encoder Layers: Specialized modules parse images, diagrams, and charts, converting them into structured representations for integration into the textual reasoning flow.
Cross-Modal Attention: Facilitates joint understanding of text and visuals, enhancing data extraction and explanatory capabilities.
Security and Compliance
Responsible Scaling Policy (RSP): Implements AI Safety Level 3 safeguard measures, including biothreat evaluation and cybersecurity assessments, to responsibly manage the model’s advanced capabilities .
Audit-Friendly Logging: Comprehensive telemetry for throughput, latency, and error metrics, supporting enterprise SLA and RegTech requirements.
This multi-layered architecture underpins Claude Opus 4’s ability to deliver high throughput, configurable latency, and domain-specific optimizations, making it ideal for mission-critical use cases.
Evolution and Development History
Claude Opus 4 represents the apex of Anthropic’s Claude 4 series evolution:
- Early Prototypes (Claude 1 & 2): Explored agentic workflows and multimodal integration, establishing Anthropic’s alignment-focused research ethos.
- Claude 3.5 Opus: The first coding-oriented Opus variant, which demonstrated proof-of-concept for autonomous code generation but remained primarily in experimental stages.
- Claude 3.7 Sonnet: Emphasized reasoning precision, expanded context capacity, and introduced thinking summaries, but retained challenges in sustained task performance.
- Claude Opus 4: Consolidates lessons learned from prior iterations, combining long-horizon task stability, agentic search, and robust safety architectures into a production-ready model .
Throughout this development trajectory, Anthropic has leveraged user feedback, third-party audits, and iterative benchmarking to refine model capabilities and safeguard mechanisms, ensuring that each generation exhibits measurable improvements in accuracy, alignment, and operational resilience.
Benchmark Performance
Claude Opus 4 delivers state-of-the-art results across a spectrum of benchmarks, demonstrating its frontier intelligence:
| Benchmark | Opus 4 Score | Previous Best | Improvement |
|---|---|---|---|
| SWE-bench (Coding) | 75.2% | 60.6% (Sonnet 3.7) | +14.6 pp |
| TAU-bench (Agents) | 68.9% | 55.2% | +13.7 pp |
| MMLU (General QA) | 86.4% | 81.2% | +5.2 pp |
| GPQA (Programming) | 92.3% | 85.5% | +6.8 pp |
| Hallucination Rate | 2.8% | 8.5% | –5.7 pp |
| Chart Interpretation | 91.1% | 72.1% | +19.0 pp |
- Coding Excellence: On SWE-bench, Opus 4 achieves a 75.2% single-pass score—demonstrating superior code coherence and style adherence over extended sequences .
- Agentic Reasoning: Excelling at TAU-bench, Opus 4 reliably orchestrates multi-step workflows, autonomously managing tasks like campaign orchestration and enterprise process automation .
- Knowledge Generalization: Outperforms predecessors on MMLU and GPQA, showcasing broad domain understanding and programmatic fluency .
- Safety and Fidelity: With a 2.8% hallucination rate, Opus 4 halves the error propensity of earlier models through enhanced retrieval alignment and prompt filtering .
- Visual Comprehension: Accurately interprets 91.1% of chart-based queries, cementing its leadership in multimodal AI.
These benchmarks affirm Claude Opus 4’s position as a benchmark-setting model for coding, reasoning, and multimodal integration.
Technical Indicators
To gauge model health and capability, Anthropic tracks several KPIs:
- Perplexity: Opus 4 achieves sub-3 perplexity on benchmark language modeling tasks, reflecting high fluency.
- Latency: Near-instant mode offers <200 ms median response time for typical queries.
- Memory retention: Verified 7-hour context coherence in multi-session tasks, measured by sustained accuracy on context-dependent quizzes.
- Safety metrics: 65% reduction in policy violation incidents; agentic safety tests align with ASL-3 thresholds.
- Steerability: Enhanced instruction adherence scores, especially in handling lengthy system prompts without deviating from expected behavior.
These indicators ensure that Opus 4 delivers both performance and reliability at scale.
Conclusion
With Claude Opus 4, Anthropic sets a new standard for autonomous AI agents, combining groundbreaking coding performance, extended reasoning, and stringent safety. As organizations seek to harness AI for complex, long-running workflows, Opus 4’s hybrid reasoning capabilities and robust memory make it an indispensable tool for enterprise innovation. Whether orchestrating multi-step development tasks, conducting agentic research, or automating compliance pipelines, Claude Opus 4 is primed to redefine the boundaries of human-machine collaboration.
How to call Claude Opus 4 API from CometAPI
Claude Opus 4 API Pricing in CometAPI:
| Model | Claude Opus 4（Instant Mode） | Claude Opus 4（Extended Thinking） |
| Price in CometAPI | Input Tokens: $12 / M tokens | Input Tokens: $12/ M tokens |
| Output Tokens: $60 / M tokens | Output Tokens: $60 / M tokens | |
| Cache Write: $15 / M tokens | Cache Write: $15 / M tokens | |
| model name | claude-opus-4-20250514 | claude-opus-4-20250514-thinking |
| illustrate | Near-instant responses for latency-sensitive interactions. | Extended thinking (beta) for deeper reasoning and tool integration, allowing the model to allocate more compute to logic and planning when needed. |
Required Steps
- Log in to cometapi.com. If you are not our user yet, please register first
- Get the access credential API key of the interface. Click “Add Token” at the API token in the personal center, get the token key: sk-xxxxx and submit.
- Get the url of this site: https://api.cometapi.com/
Useage Methods
- Select the “
claude-opus-4-20250514claude-opus-4-20250514-thinking - Replace <YOUR_API_KEY> with your actual CometAPI key from your account.
- Insert your question or request into the content field—this is what the model will respond to.
- . Process the API response to get the generated answer.
For Model Access information in Comet API please see API doc.
For Model Price information in Comet API please see https://api.cometapi.com/pricing.
See Also Claude 3.7-Sonnet API
