Nano Banana

Nano Banana is the community's name for Google's Gemini-native image generation - it started as an anonymous codename on the HuggingFace leaderboard, Google leaned into the banana memes, and the name stuck as official branding. This node is the way to run it from inside ComfyUI with just a Gemini API key, and it's probably the most talked-about node in this pack. The KB sums up the character of the model well: technically impressive, unexpectedly good at creative/editorial image work, and aggressively censored ("powerful, unimaginative, massive hidden biasing" is the recurring community complaint).

What makes Nano Banana worth reaching for: it's genuinely creative in a way most local models aren't - stylized edits, multi-image reference compositing, strong prompt understanding. It's the model people use for "make this look like a Pixar poster" style transformations that a local Flux stack would fight you on.

How it works

The node uses the google-genai SDK (genai.Client with your Gemini key) and calls models.generate_content() with your prompt, optional reference images (up to five), and generation config (aspect ratio, resolution, sampling). Reference images are converted in memory and passed as image parts. The result comes back as bytes, decoded into a Comfy IMAGE.

The inputs that matter

• prompt - the creative input. Be vivid; the model rewards descriptive direction.
• model - three tiers: gemini-3-pro-image-preview (Nano Banana Pro - the flagship, 4K-native and the one with "thinking" baked in), gemini-2.5-flash-image (the original Nano Banana), and gemini-3.1-flash-image-preview (Nano Banana 2, the speed hybrid). Default to the 2.5 flash image for cheap iteration; reach for Pro for finals.
• aspect_ratio - eight options from 1:1 to 21:9 (plus the 2:3/3:2/3:4/4:3/9:16/16:9 range).
• resolution - 1K, 2K, or 4K. 4K is the Pro model's party trick, and the price multiplier.
• temperature (default 0.5) and top_p (default 0.85) - the sampling dials. Lower for consistent results.
• google_search - on/off; lets the model ground on live web results. Niche; mostly off.
• system_instruction (optional) - steer the style up front.
• image_1..image_5 (optional) - attach one or more reference images and this becomes editing/referencing: style transfer from image A, character consistency from image B, multi-image composition. This is where Nano Banana's reputation was built.
• seed / api_key - key in the field or .env (GEMINI_API_KEY).

The output

image - a single IMAGE output, into preview/save.

Installing it

One of ~20 nodes in the Aryan185/ComfyUI-ExternalAPI-Helpers pack:

cd ComfyUI/custom_nodes
git clone https://github.com/Aryan185/ComfyUI-ExternalAPI-Helpers.git
cd ComfyUI-ExternalAPI-Helpers
pip install -r requirements.txt

Restart ComfyUI; find "Nano Banana" under image/generation. Needs google-genai. Gemini key from aistudio.google.com - in the field or via GEMINI_API_KEY in .env. Note that r/comfyui folk do use this exact pack to run Nano Banana through ComfyUI, alongside the official Comfy API nodes - it's a known, working route.

Where people get burned

The censorship is the thing, full stop. Google's IMAGE_SAFETY filtering got stricter in early 2026, and famous IP/celebrity requests are heavily restricted. You'll get refusals on prompts that feel innocent, and unlike a local model there's no bypass - it's the API's policy. Plan around it. Also, cost: 4K Pro generations are the most expensive images in this pack, so do your iteration at 1K on the flash model. And the seed is for ComfyUI caching, not API reproducibility.

Despite the filters, this is the node people actually have fun with. The multi-image referencing alone justifies installing the pack.