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., --size only on Gemini 3, 512 resolution only on nanobanana-2)
  • Custom Gemini-compatible gateway support via --base-url and 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

  1. Open references/config.md to choose environment variables and override order.
  2. Open references/models-and-api.md to pick the right Nano Banana tier and check model-specific constraints.
  3. 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).
  4. Run scripts/nanobanana.py generate for one request or scripts/nanobanana.py batch for repeated variants.
  5. Add --dry-run first when the main risk is the payload shape, endpoint, or model-specific option support.
  6. Pass --base-url or GEMINI_BASE_URL when you need a custom Gemini-compatible gateway.
  7. Add --save-response <path> on generate when you need the raw JSON body for debugging.

Commands

Single text-to-image request:

Installs
10.3K
GitHub Stars
3
First Seen
Apr 23, 2026
nanobanana — gargantuax/openskills