Clean and classify in bulk
Normalize formats, assign topics, and add labels so raw text becomes filterable data.
Gemini Data ProcessingText and data processing
Turn messy text into structured data with Gemini
Classify, summarize, translate, and extract structured data through an OpenAI-compatible endpoint. Use it after collection or with data you already have.
- 7
- supported model IDs
- OpenAI
- API compatibility
POST /api/v1/chat/completionsFrom raw text to structured data
01Raw text and target fieldsText and data processing
02Call Gemini Data ProcessingPOST /api/v1/chat/completions
03Classification, summary, or JSON fieldsReady for analytics or business systems
Ready for analytics or business systems
Process data right after collection
Specify the output structure instead of writing a new ruleset for every batch, then send the result to the next step.
Summarize, translate, and rewrite
Condense long text into key points and normalize language for review and analysis.
Extract JSON fields
Return entities, attributes, and decisions as JSON your database or workflow can use.
Choose a compatible model ID for the task
Start with the default fast model. Choose a thinking-compatible model ID when the task needs additional reasoning.
Keep your OpenAI SDK and change the base URL
The endpoint accepts the OpenAI chat completions request shape. Agents can use the same text-processing capability through MCP.
Per-request pricing for batch workloads
Each request is charged at the current model route. Invalid, failed, or empty requests are not charged, and the final amount is visible in the console.
View full pricing- Current public price
- $1.74 per 1,000 requests
Use a real batch to validate your first structured result
Start with the default model and the fields your workflow actually needs, then expand to batch processing.