Node Based Image Generation

It is a way to make AI images by connecting visual steps on a canvas. A prompt feeds a model; the image can then feed an upscaler, editor or background remover. You can save the graph and reuse the structure with new inputs.

No local GPU is needed for Wireflow's hosted models. Build and run the workflow in your browser. Model limits, output settings and credit costs still apply.

A node workflow keeps the production steps visible and reusable. Instead of stopping at one generated image, you can connect editing or processing stages, change a model and keep the rest of the structure.

The linked template starts with GPT Image 2.5 Flare. Other supported image models include Nano Banana 2 and Flux 2 Pro. Choose from the current node picker and match the model's input ports and settings to your workflow.

Yes. Workflows save as you edit. Reopen a graph with a new prompt or input, share it with the appropriate permissions, or run your own saved copy through the API.

Yes. The REST API can run a workflow you own with new inputs and an API key. It returns an execution ID that your code polls for the output, making the same graph useful in an automated process.

Yes. Add a supported upscaling node and connect the generated image to its image input. Choose the scale and settings that node supports. Upscaling is an optional addition to the starter template and has its own credit cost.

Start with the two-node template and add only the stages the job needs. Wireflow's API documentation lists a validation limit of 100 nodes and 500 edges per workflow. Larger graphs also involve more model limits, settings and generation costs to manage.