Anthropic: Claude Opus 4
Anthropic: Claude Opus 4
Master Complex Reasoning Tasks
Top Coding Model
Sustained Long-Running Performance
Handles thousands of steps in agent workflows for engineering and research.
Hybrid Reasoning
Extended Thinking Mode
Switches between instant responses and deep analysis for precise problem-solving.
Memory Enhanced
Autonomous Agent Building
Creates memory files for long-term coherence in multi-session tasks.
Examples
See what Anthropic: Claude Opus 4 can create
Copy any prompt below and try it yourself in the playground.
Code Refactor
“Refactor this Python function for efficiency, handling edge cases with error logging and type hints. Preserve original functionality while optimizing loops and memory usage.”
Agent Workflow
“Design autonomous agent to analyze sales data: query database, identify trends, generate report with charts, and suggest optimizations step-by-step.”
Research Synthesis
“Synthesize key insights from quantum computing papers: summarize advancements, compare approaches, predict future impacts on cryptography.”
Debug Session
“Debug this Node.js app crashing on high load: trace memory leaks, profile performance, propose fixes with tests for scalability.”
For Developers
A few lines of code.
Opus 4. One API call.
ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.
- Serverless: scales to zero, scales to millions
- Pay per token, no minimums
- Python and JavaScript SDKs, plus REST API
import requestsresponse = requests.post("https://modelslab.com/api/v7/llm/chat/completions",json={"key": "YOUR_API_KEY","prompt": "","model_id": ""})print(response.json())
Ready to create?
Start generating with Anthropic: Claude Opus 4 on ModelsLab.