nano-banana-2

name	nano-banana-2
displayName	Nano Banana 2 — Pro Pack on RunComfy
description	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 typography rendering, predictable framing, optional web-grounded context), the resolution-tier pricing, the safety-tolerance dial, and when to route to Nano Banana Pro / GPT Image 2 / Flux 2 / Seedream instead. Calls `runcomfy run google/nano-banana-2/text-to-image` through the local RunComfy CLI. Triggers on "nano banana", "nano-banana-2", "nano banana 2", "google image gen", "gemini image", or any explicit ask to generate with this model.
homepage	https://www.runcomfy.com
license	MIT

Nano Banana 2 — Pro Pack on RunComfy

runcomfy.com · Model page · GitHub

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.

npx skills add agentspace-so/runcomfy-skills --skill nano-banana-2 -g

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 skill.

How to invoke

Default draft (1K, square, png):

runcomfy run google/nano-banana-2/text-to-image \
  --input '{"prompt": "<user prompt>"}' \
  --output-dir <absolute/path>

Vertical 4-up batch for ideation:

runcomfy run google/nano-banana-2/text-to-image \
  --input '{
    "prompt": "<user prompt>",
    "num_images": 4,
    "aspect_ratio": "9:16",
    "resolution": "0.5K"
  }' \
  --output-dir <absolute/path>

Final at 2K with seed lock:

runcomfy run google/nano-banana-2/text-to-image \
  --input '{
    "prompt": "<user prompt>",
    "resolution": "2K",
    "aspect_ratio": "16:9",
    "seed": 42
  }' \
  --output-dir <absolute/path>

Web-grounded (current event / real entity):

runcomfy run google/nano-banana-2/text-to-image \
  --input '{
    "prompt": "<prompt referencing a real-world event from this week>",
    "enable_web_search": true
  }' \
  --output-dir <absolute/path>

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):

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

Brand-asset card with quoted text:

A minimalist 16:9 product card: a matte black ceramic mug centered on a
soft warm-grey paper background, rim highlight from upper-left, the
headline "Brewed Quietly" in clean bold sans-serif top-right, balanced
negative space below, e-commerce ready, clean studio lighting

Vertical platform-native:

A 9:16 vertical hero for a wellness brand: a single ceramic teacup on a
linen runner, soft morning side-light, the words "Slow Down" in
hand-drawn serif large at the top, gentle steam rising, neutral color
palette, uncluttered

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.

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.