Local image generation

Local image generation means running open diffusion models on your own graphics card or Mac instead of typing prompts into a website. Your prompts, reference images and results stay on your drive, there is no per-image fee, and you can use models, styles and settings that hosted services do not offer.

The interfaces range from a single prompt box to full node graphs. Simple apps suit people who want a picture from a sentence with a few sliders for size and style. Canvas-based tools add layers, masks and brushes for fixing part of an image or extending it past its edges. Node-based tools show every step of the process as a box you can rewire, which makes complex chains repeatable and shareable as files.

Hardware decides what you can run. Image models lean heavily on the GPU, and newer, larger models need more video memory than older ones. Apple silicon Macs run many models through their shared memory, often more slowly than a dedicated PC card. Most interfaces offer memory-saving options that trade speed for the ability to run on smaller cards.

Pay attention to where model files and add-ons come from. Image interfaces support community extensions and custom nodes, and each one is code that runs with your user's permissions. Model files in the older pickle format can also run code when loaded. Prefer safetensors files, install extensions from sources with an active history, and keep your interface updated.

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7 local AI tools in local image generation

ComfyUI

by Comfy Org

A node-based interface for building image and video generation workflows with open diffusion models on your own GPU.

  • Open source
  • Works offline after setup
  • Runs on macOS

Invoke

An image generation app with a layered canvas for inpainting, outpainting and editing, available as a free local edition.

  • Open source

SwarmUI

by mcmonkeyprojects

A web interface for image generation that offers a simple prompt tab on top of a ComfyUI backend for advanced work.

  • Open source

Stable Diffusion WebUI Forge

by lllyasviel

A fork of the classic Stable Diffusion web UI that focuses on lower memory use and faster generation.

  • Open source

SD.Next

by vladmandic

A web interface for image and video diffusion models with support for several GPU vendors and backends.

  • Open source

Mochi Diffusion

A native Mac app that runs Stable Diffusion models converted to Core ML, using the Neural Engine on Apple silicon.

  • Open source
  • Works offline after setup
  • Runs on macOS

Draw Things

An image generation app for Mac, iPhone and iPad that runs diffusion models fully on the device.

  • Works offline after setup
  • Runs on macOS

Licenses vary more here than anywhere else in local AI. Some open image models allow commercial use, some limit it to smaller organizations, and some are research-only. Fine-tuned models built on a base model usually inherit its terms. If images will be sold, published by a business or used in client work, read the license of every model in the chain.

Disk space disappears quickly in this category. Image models, add-on style files and upscalers each take gigabytes, and node-based tools encourage collecting many of them. Keep models in one shared folder that several interfaces can read, delete ones you no longer use, and note where each file came from so you can check its license later without guessing.

Finally, think about how you will keep your work. Many interfaces save the settings used for each image inside the file or alongside it, which lets you reproduce a result later. Keep those settings when you share or archive images.

Questions about local image generation

Can I generate images locally on a laptop?

Yes, with limits. Apple silicon laptops and gaming laptops with a dedicated GPU handle many models. Thin laptops without a graphics card can run small models very slowly. Start with an older, smaller model and the interface's low-memory settings.

Are custom nodes and extensions safe to install?

Treat them like any software download. Each extension runs code on your machine. Install only what you need, prefer projects with an active history and many users, and update or remove ones that are no longer maintained.

Can I sell images made with open models?

It depends on the model license, not the interface. Some licenses allow commercial use, some restrict it, and fine-tuned models usually carry the base model's terms. Read the model page before using images commercially.

Why do the same settings give a different image?

Results depend on the seed, the model version, the sampler and sometimes the hardware and software versions. Save the full settings with each image if you need to reproduce it later.

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