Edit images with Google Nano Banana 2 (image-to-image edit endpoint) on RunComfy. Documents Nano Banana Edit's strengths (preserve subject identity, swap background, localize edits with spatial language, multi-image batch edits up to 20 inputs), the schema, and when to route to GPT Image 2 edit / Fl

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. 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: Batch edit with locked framing: Targeted spatial edit ("left object only"): 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 gallery — same product on different backgrounds Batch of 20, identity preserved, framing locked Influencer / spokesperson background swaps Strong identity preservation across edits Localized object removal / addition Spatial language honored A/B variants for ad creative Seed lock + multiple number of images Brand asset relocalization Same composition with text / palette swap Sample prompts (verified to produce strong results) Background swap (page example): Targeted text replacement: Multi image batch consistency: Limitations 1–20 input images per call — the first is treated as primary; the rest provide auxiliary cues. 1–4 outputs per call. Long compound prompts drift — split into multiple passes. Web search adds latency + cost — only enable on demand. For multilingual in image text edits, GPT Image 2 edit wins. Exit codes code meaning 0 success 64 bad CLI args 65 bad input JSON / schema mismatch 69 upstream 5xx 75 retryable: timeout / 429 77 not signed in or token rejected Full reference: [docs.runcomfy.com/cli/troubleshooting](https://docs.runcomfy.com/cli/troubleshooting?utm source=skills.sh&utm medium=skill&utm campaign=nano banana edit). How it works The skill invokes runcomfy run google/nano banana 2/edit with a JSON body matching the schema. The CLI POSTs to https://model api.runcomfy.net/v1/models/google/nano banana 2/edit , polls the request, fetches the result, and downloads any .runcomfy.net / .runcomfy.com URL into output dir . Ctrl C cancels the remote request before exit. Security & Privacy Token storage : runcomfy login writes the API token to ~/.config/runcomfy/token.json with mode 0600 (owner only read/write). Set RUNCOMFY TOKEN env var to bypass the file entirely in CI / containers. Input boundary : the user prompt is passed as a JSON string to the CLI via input . The CLI does NOT shell expand the prompt; it transmits the JSON body directly to the Model API over HTTPS. No shell injection surface from prompt content. Third party content : image / mask / video URLs you pass are fetched by the RunComfy model server, not by the CLI on your machine. Treat external URLs as untrusted; image based prompt injection is a known risk for any image edit / video edit model. Outbound endpoints : only model api.runcomfy.net (request submission) and .runcomfy.net / .runcomfy.com (download whitelist for generated outputs). No telemetry, no callbacks. Generated file size cap : the CLI aborts any single download 2 GiB to prevent disk fill from a malicious or runaway model output.

nano-banana-edit