Gemini-style models can be cost-effective, but token usage can add up. This post outlines practical tactics:
- Select the correct model and use per-model token estimates in the app.
- Use Token Compression to remove redundancy and boilerplate.
- Batch multiple short prompts in one request where semantically appropriate.
- Prefer concise system prompts and structured inputs (JSON) to avoid verbose natural language framing.
See Token Compression and Model selector in the app for hands-on tools to reduce spend.