Nano Banana Edit

# Nano Banana Edit — Pro Pack on RunComfy

[runcomfy.com](https://www.runcomfy.com/?utm_source=skills.sh&utm_medium=skill&utm_campaign=nano-banana-edit) · [Edit endpoint](https://www.runcomfy.com/models/google/nano-banana-2/edit?utm_source=skills.sh&utm_medium=skill&utm_campaign=nano-banana-edit) · [GitHub](https://github.com/agentspace-so/runcomfy-skills/tree/main/nano-banana-edit)

Google **Nano Banana 2 Edit** — the image-to-image edit endpoint of the Gemini-family flash-tier image model — hosted on the **RunComfy Model API**. Up to **20 input images per call** for batch edits and multi-reference variation.

```bash npx skills add agentspace-so/runcomfy-skills --skill nano-banana-edit -g ```

## When to pick this model (vs siblings)

| You want | Use | |---|---| | Preserve subject identity, swap background or clothing | **Nano Banana Edit** | | Edit up to 20 images consistently in one batch | **Nano Banana Edit** | | Localize edit to "X only" with spatial language | **Nano Banana Edit** | | Edit multilingual text inside the image (signs, labels) | GPT Image 2 edit | | Single ref + precise local edit ("she's now holding X") | Flux Kontext | | Generate a new image from scratch | Nano Banana 2 t2i (sibling skill) |

If the user said "nano banana edit" / "edit with nano banana" explicitly, route here regardless.

## Prerequisites

1. **RunComfy CLI** — `npm i -g @runcomfy/cli` 2. **RunComfy account** — `runcomfy login` opens a browser device-code flow. 3. **CI / containers** — set `RUNCOMFY_TOKEN=<token>` instead of `runcomfy login`.

## Endpoints + input schema

### `google/nano-banana-2/edit`

| Field | Type | Required | Default | Notes | |---|---|---|---|---| | `prompt` | string | yes | — | Edit instruction. Lead with preservation, end with the change. | | `image_urls` | array | yes | — | **1–20** publicly-fetchable HTTPS URLs. | | `number_of_images` | int | no | 1 | 1–4 outputs per call. | | `seed` | int | no | — | Reproducibility. | | `aspect_ratio` | enum | no | `auto` | `auto` (follows input) or fixed ratios — lock for batch consistency. | | `resolution` | enum | no | `1K` | `0.5K` / `1K` / `2K` / `4K`. | | `output_format` | enum | no | `png` | `png` / `jpeg` / `webp`. | | `safety_tolerance` | int | no | 4 | 1 (strict) – 6 (permissive). | | `limit_generations` | bool | no | — | If true, restricts each round to one output. | | `enable_web_search` | bool | no | false | Web grounding (extra cost / latency). |

## How to invoke

**Single-image background swap, identity preserved:**

```bash runcomfy run google/nano-banana-2/edit \ --input '{ "prompt": "Keep the subject identity, pose, and clothing unchanged. Convert the background into a rainy neon cyberpunk street.", "image_urls": ["https://.../portrait.jpg"] }' \ --output-dir <absolute/path> ```

**Batch edit with locked framing:**

```bash runcomfy run google/nano-banana-2/edit \ --input '{ "prompt": "Replace the watermark in the bottom-right with the text \"AURA\" in clean white sans-serif. Keep everything else exactly as in the input.", "image_urls": ["https://.../sku-1.jpg", "https://.../sku-2.jpg", "https://.../sku-3.jpg"], "aspect_ratio": "1:1", "resolution": "1K" }' \ --output-dir <absolute/path> ```

**Targeted spatial edit ("left object only"):**

```bash runcomfy run google/nano-banana-2/edit \ --input '{ "prompt": "Remove the leftmost object only. Keep the right two objects, the table, and the lighting unchanged.", "image_urls": ["https://.../still-life.jpg"] }' \ --output-dir <absolute/path> ```

## Prompting — what actually works

**Preservation first, change last.** Always lead with `"Keep [identity / pose / clothing / brand / framing] unchanged."` Then state the change in one clean sentence. Models honor what's stated up front; tail-end preservations get ignored.

**Localize with spatial language.** "background only", "the left object", "the upper-right corner", "above the headline" — concrete spatial scopes are honored. "make it more X" is vague and drifts.

**Batch consistency** — when editing a series, lock `aspect_ratio` and `resolution`. Use the same prompt grammar across the batch so each output reads as a sibling, not a remix.

**Iterate small.** If a one-pass edit drifts, split into two: pass 1 changes background only, pass 2 swaps the subject's outfit. Cleaner edits, same total cost (assuming similar resolution).

**Multi-image variation** — pass up to 20 inputs to get a coherent batch. Useful for SKU galleries, A/B testing, character sheet variations.

**Anti-patterns:** - Long compound instructions ("change A and B and C and D") — drift increases per added scope. - Edit instructions written in passive voice ("the background should be changed") — be imperative. - Missing preservation goals — model will subtly rewrite the face / brand. - Aspect ratios that don't match input — causes crops or stretches.

## Where it shines

| Use case | Why Nano Banana Edit | |---|---| | **SKU gal