arkennemasis fal · Nano Banana 2 Lite · ~$0.05/image

Why you'd want a closed model in the graph

Nano Banana is Google's Gemini-native image generation, and you cannot download it. There are no weights, no local checkpoint, no quantized GGUF that will ever exist for it. If you want its look, its prompt understanding, or its text rendering, you call it. This node is that door.

The reason it belongs in a ComfyUI graph rather than a browser tab is the hybrid workflow everyone settled on: generate the frame with the closed model, animate it with an open one. The r/StableDiffusion pattern is literally "closed Google model for the still, open Wan model for the motion" - you get the quality you can't run, next to the upscaler, masker and video graph you can. This node drops the image straight into your canvas as a normal IMAGE.

"Lite" is the efficiency member of the family: sub-2-second class latency, fixed 1K (1024×1024) output, and 14 aspect ratios including absurd ones like 8:1 and 1:8. It costs about $0.05 per image. If you were expecting Nano Banana Pro's 4K and thinking mode, that's a different model - Lite is the one you spam.

How it works

Nothing runs on your GPU. The node wraps fal's google/nano-banana-2-lite endpoint: it sends your prompt (plus a system instruction, if you set one), submits one billed request, polls while showing status on the node, then downloads the results into output/fal/google_nano-banana-2-lite/ and hands you an IMAGE batch. ComfyUI's Cancel cancels on fal.

Inputs worth setting

• prompt - the whole point. Write it like you're talking to Gemini, not to an SDXL checkpoint: full sentences beat tag soup here.
• aspect_ratio - auto (default) lets the model choose from your prompt, which is usually right. The extreme ratios (4:1, 1:4, 8:1, 1:8) are genuinely useful for banners and long strips that would otherwise need an outpaint chain.
• num_images - 1 to 4 per call. Four separate pictures, same prompt, billed per image.
• output_format - png (default), jpeg, webp. If the images go straight into a video pipeline, jpeg saves you disk for no visible loss.
• system_prompt - a real system instruction to the model, not a prompt prefix. Set it once with your house style and leave it. Empty leaves it out.
• safety_tolerance - 1 to 6, default 4. 1 blocks most things; 6 is the loosest Google's endpoint will go. Note that looser is still Google's filter, not no filter.
• thinking_level - (not set), minimal, or high. Turning thinking on makes the model reason about the prompt before drawing, and it gets included in the generation. It's off by default and I'd leave it off until a prompt genuinely needs it.
• limit_generations - on by default, and it forces one image per round of prompting, ignoring any "give me four variations in this one picture" instructions. It's marked experimental and can affect quality. Turn it off if your prompt deliberately asks for a grid.

And the guards: max_cost_usd ($20 default, 0 = off), reuse_identical_run (won't re-bill identical inputs, even after a restart), extra_json (escape hatch for fal fields the node has no box for), max_concurrent (default 1 - one paid fal call at a time across the whole graph).

Outputs

• images - the IMAGE batch, straight into a Save Image, an upscaler, or Wan/Flux image-to-video.
• image_paths - the saved files as strings.
• description - fal's text for the result, useful if you're piping captions somewhere.
• info - request id, estimate, saved files, fal's raw answer.

Install

cd ComfyUI/custom_nodes
git clone https://github.com/Hishamahmer/comfyui-arkennemasis
pip install -r comfyui-arkennemasis/requirements.txt

Restart ComfyUI afterwards, or install via ComfyUI-Manager with the Git URL. The only declared dependency is httpx, and the fal half of the pack doesn't even need that - it talks to fal with the standard library.

Add the key once to the .env next to run_nvidia_gpu.bat (or the ComfyUI folder):

FAL_KEY=your-key-from-fal.ai/dashboard/keys

Where people get burned

The ~$0.05/image tag is an estimate, not a rate card. This endpoint bills by tokens - input and output text tokens, and image tokens at $37.50 per million on the way out. The node's price badge assumes a normal one-image, one-prompt request. A monster prompt asks for a monster bill, so watch the pre-run estimate rather than trusting the tag.

Fixed 1K output is the real constraint. Every Lite image comes out at 1024×1024-class resolution regardless of the aspect ratio you pick, so the wide ones aren't hi-res wide, they're 1K wide with less height. Plan on a local upscaler in the chain if the output needs to be big.

The safety filter is Google's, and you can't patch it. Google's image line is among the most aggressively filtered in the field, which is the single most common reason people give for staying local. safety_tolerance nudges it; it doesn't remove it. Prompts that trip it will fail, and no custom node can change that.

Your prompt leaves your machine. That's the mechanism of an API node, not a bug in it - and given this category's history, a fresh wrapper pack is a thing to read before you run it, not to install blind.