nanobanana
Installation
Summary
Gemini-native text-to-image and image editing with three model tiers, batch generation, and custom gateway support.
- Three model aliases (
nanobanana,nanobanana-2,nanobanana-pro) map to distinct Gemini image models with different speed, cost, and fidelity tradeoffs - Supports single generation, batch variants, multi-image editing with local file references, and dry-run request inspection before sending
- Strict option validation enforces model-specific constraints (e.g.,
--sizeonly on Gemini 3,512resolution only onnanobanana-2) - Custom Gemini-compatible gateway support via
--base-urland flexible auth modes for self-hosted or proxied endpoints
SKILL.md
Nano Banana
A single Python entrypoint for Gemini-native Nano Banana image generation and editing, with model aliases, strict option validation, batch runs, and custom endpoint support.
Workflow
- Open references/config.md to choose environment variables and override order.
- Open references/models-and-api.md to pick the right Nano Banana tier and check model-specific constraints.
- Prefer
gemini-3.1-flash-image-preview(nanobanana-2) unless you need either the fastest low-cost default (nanobanana) or the highest-fidelity reasoning model (nanobanana-pro). - Run
scripts/nanobanana.py generatefor one request orscripts/nanobanana.py batchfor repeated variants. - Add
--dry-runfirst when the main risk is the payload shape, endpoint, or model-specific option support. - Pass
--base-urlorGEMINI_BASE_URLwhen you need a custom Gemini-compatible gateway. - Add
--save-response <path>ongeneratewhen you need the raw JSON body for debugging.
Commands
Single text-to-image request: