AI Image Generation

Last reviewed Aug 26, 2026 · 417 words

Buy (or already own) the GPU before you shortlist anything here: every serious self-hosted image generator lists 8 GB of system RAM as the floor, and in practice a dedicated GPU with 6–8 GB of VRAM is the difference between seconds per image and minutes. CPU-only generation technically works and is fine for proving the pipeline, not for actual use. Once the hardware exists, the choice is almost purely about interface philosophy.

How to choose an image generation tool

The axis that matters is control versus convenience. At one end, Fooocus (GPL-3.0, 52,538 stars) deliberately hides the machinery: type a prompt, get a good image, with automatic prompt expansion and style presets doing the tuning Midjourney does for you. At the other, ComfyUI (GPL-3.0, 129,995 stars) exposes generation as a node graph you wire yourself — more to learn, but pipelines become shareable files, VRAM use is notably efficient, and it supports SD, SDXL, Flux, and video models. The second axis is maintenance reality, which in this category diverges from popularity: check release activity before committing to an extension ecosystem you will depend on.

Where to start

Fooocus for a first-timer wanting Midjourney-quality output with minimal setup; its honest limitation is coarse control. ComfyUI when you outgrow that — inpainting chains, LoRA stacks, reproducible workflows — and are willing to spend an evening learning the graph. The famous third option, Stable Diffusion WebUI by AUTOMATIC1111, remains the category's largest at 164,668 stars with a huge extension catalogue, but releases have been infrequent lately; its Forge fork keeps the familiar UI while improving speed, lowering VRAM use, and adding Flux support, and takes most A1111-compatible extensions. New installs wanting that interface should start with Forge.

The training detour

Generating images and training models are different hobbies. LoRA and fine-tuning tools live at the hard end of this category — 16 GB of RAM, serious VRAM, and Python patience — and nothing about running Fooocus prepares you for them. Get comfortable generating with community models from Civitai and Hugging Face first; most people never need to train at all.

What I'd do

Fooocus on day one to confirm the GPU earns its keep, then ComfyUI as the long-term install — its workflows are the closest thing this category has to infrastructure you can version-control. I would only reach for A1111/Forge if a specific extension demands it.