Export CSV from Claude Console
AI Models & Assistants / Knowledge library
Claude 3.7 Sonnet
Claude 3.7 Sonnet is a versioned Claude language model. Consult its lifecycle and model documentation before selecting it.
Why learn Claude 3.7 Sonnet?
Offers the documented Anthropic model capabilities through hosted.
The problem it solves
Provides model inference for supported text inputs.
Where it came from
Claude 3.7 Sonnet: Claude 3.7 Sonnet is a versioned Claude language model. Consult its lifecycle and model documentation before selecting it. Published aliases: claude-3-7-sonnet-20250219. Input: text. Output: consult source. Checked 2026-10-13. Model capabilities are distinct from tools available in a particular agent.
Build your understanding
Work through these exercises in order. Try the task before opening a reference.
- Explain what Claude 3.7 Sonnet does.
- Identify a use case for Claude 3.7 Sonnet.
- Describe a limitation of Claude 3.7 Sonnet.
- Name a compatible tool for Claude 3.7 Sonnet.
- Compare Claude 3.7 Sonnet against an alternative.
Documentation and sources
- Primary source / model card (platform.claude.com)
Catalog research notes
- See the AI Workbench for source dates, pricing evidence and configuration details.
Connect the ideas
Built on
Real World Example
Lifecycle Management for Legacy Claude Integrations
Enterprise software teams maintaining long-running automated document processing pipelines.
The business problem
Applications relying on retired models like claude-3-7-sonnet-20250219 experience service failures because requests to retired models will fail.
How this topic solves it
Teams must audit API usage via the Claude Console to identify deprecated model calls and migrate workloads to active, supported models such as claude-sonnet-5-5 to maintain service continuity.
- Access the Usage page in the Claude Console to export API activity logs.
- Filter the CSV export to identify instances where the application is still using retired or deprecated model IDs.
- Update the application codebase to reference an active, supported model identifier.
- Perform thorough testing of the application with the new model to ensure output consistency before full deployment.
The process of identifying and replacing retired model dependencies.
Locate retired model IDs
Replace model ID in API calls
Test against new model
- Usage Audit → extracts data → Identification
- Identification → triggers refactor → Code Update
- Code Update → verifies stability → Validation
Expected business outcome
Restored service reliability and alignment with current model support standards, preventing unexpected downtime from model retirement.
Limitations and checks
Migrating to a newer model may introduce variations in output behavior; teams must perform thorough testing of your applications with the new models well before the retirement date to verify performance.