Generate images with Google Nano Banana 2 (Gemini-family flash-tier text-to-image) on RunComfy — bundled with the model's documented prompting patterns so the skill gets sharper output than naive prompting against the same model. Documents Nano Banana 2's strengths (rapid iteration, in-image typogra

Nano Banana 2 — Pro Pack on RunComfy [runcomfy.com](https://www.runcomfy.com/?utm source=skills.sh&utm medium=skill&utm campaign=nano banana 2) · [Model page](https://www.runcomfy.com/models/google/nano banana 2?utm source=skills.sh&utm medium=skill&utm campaign=nano banana 2) · [GitHub](https://github.com/agentspace so/runcomfy skills/tree/main/nano banana 2) Google Nano Banana 2 — the flash tier text to image model in the Gemini family — hosted on the RunComfy Model API . Optimized for ideation, social thumbnail batches, and rapid drafts with strong in image typography. When to pick this model (vs siblings) Nano Banana 2 is the flash tier of the Google image gen line. Pick it when iteration speed and predictable framing matter more than maximum detail. You want Use Rapid drafts, social thumbnails, batch variants Nano Banana 2 In image typography with predictable rendering Nano Banana 2 Web grounded image (current events / real entities) Nano Banana 2 + enable web search Image edit (preserve subject, swap background) Nano Banana Edit (sibling skill) Heavy stylization, painterly look Flux 2 Maximum prompt adherence + multilingual text GPT Image 2 2K–4K hero shots, max realism Seedream 5 Hyperrealistic portrait Nano Banana Pro If the user said "Nano Banana" / "nano banana 2" / "Gemini image" explicitly, route here regardless. If they said "Nano Banana" without specifying 2 vs Pro, default to Pro for portraits and 2 for everything else. 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/text to image Field Type Required Default Notes prompt string yes — Subject first description. num images int no 1 1–4. Use 4 for ideation rounds. seed int no 0 Reuse for reproducibility. aspect ratio enum no auto auto , 21:9 , 16:9 , 3:2 , 4:3 , 5:4 , 1:1 , 4:5 , 3:4 , 2:3 , 9:16 . resolution enum no 1K 0.5K (drafts), 1K (default), 2K (final), 4K (max). output format enum no png png , jpeg , webp . safety tolerance int no 4 1 (strict) – 6 (permissive). limit generations bool no true Limit each prompt round to one generation. enable web search bool no false Adds web grounding (extra cost + latency). For image edit (preserve subject + apply changes), see the sibling [ nano banana edit ](../nano banana edit) skill. How to invoke Default draft (1K, square, png): Vertical 4 up batch for ideation: Final at 2K with seed lock: Web grounded (current event / real entity): Prompting — what actually works Subject first declarative grammar. "A cinematic close up portrait of an American woman standing under neon lights in rainy Tokyo, shallow depth of field, reflective wet streets, ultra detailed, realistic skin texture" — primary subject, then action, environment, style, camera. Front load subject; trail with directives. Exact text quoting for in image typography. "The label reads 'AURA' in clean bold sans serif, centered, white on black" — quote the literal characters. Specify placement and font style. Don't say "with the brand name on it" and hope. Consistent seeds for refinement. Lock seed when iterating a single prompt across small variants — keeps composition stable. Web grounding, sparingly. Turn on enable web search only when the prompt names current events / real entities. Adds latency + cost; off by default. Don't conflict styles. "minimalist + ornate + retro + cyberpunk" cancels. Pick 1–2 anchors. Anti patterns: Trying to verbally describe a stable subject identity — use the edit endpoint with image refs instead. Asking for resolutions outside the 4 tiers → 422. Aspect ratios outside the 11 supported values → 422. Non quoted in image text → unpredictable rendering. Where it shines Use case Why Nano Banana 2 Marketing draft thumbnails (batch of 4) Fast iteration at 0.5K, then promote winner to 2K Social platform native Wide aspect ratio support including 9:16, 4:5, 21:9 In image typography for posters / cards Predictable text rendering when characters are quoted Web grounded current event imagery enable web search integrates fresh info Reproducible variant testing Strong seed + consistent framing Sample prompts (verified to produce strong results) Cinematic portrait (page example): Brand asset card with quoted text: Vertical platform native: Limitations Still images only. No video on this endpoint. Max 4 outputs per request. Web search adds latency + cost — only enable on demand. 2K / 4K cost more — default to 1K unless user asked for higher. For image edit, use the /edit endpoint — not this one. 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 2). How it works The skill invokes runcomfy run google/nano banana 2/text to image with a JSON body matching the schema. The CLI POSTs to https://model api.runcomfy.net/v1/models/google/nano banana 2/text to image , 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-2