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📖 The AI Tool Bible

Flux vs Stable Diffusion Web UI (AUTOMATIC1111)

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

 
Flux
Image Generation
Stable Diffusion Web UI (AUTOMATIC1111)
Image Generation
TaglineBlack Forest Labs' open-weights image model — rivals Midjourney quality.The de facto local Stable Diffusion power-user UI.
CategoryImage GenerationImage Generation
PricingFreemium· FLUX.2 [max]: $0.07 · FLUX.2 [pro]: $0.03 · FLUX.2 [klein] 9B: $0.015 · FLUX.2 [klein] 4B: $0.014 · FLUX.2 [flex]: $0.05Free· Free / open-source (AGPL-3.0). You provide your own compute (local GPU, rented cloud GPU, or a Colab instance).
ModelFlux.1 [schnell / dev / pro]Stable Diffusion 1.x / 2.x / SDXL and community fine-tunes (Safetensors checkpoints)
Editorial score9.0 / 10
Use cases
open sourceself-hostedhigh quality
Local text-to-image generationInpainting and outpainting existing imagesLoRA and textual inversion trainingControlNet-guided composition (pose, depth, edges)Batch prompt exploration with X/Y/Z gridsUpscaling and face restoration passesConcept art and illustration referenceCheckpoint merging and model experimentation
Pros
  • Open weights for [schnell]/[dev] variants
  • Quality rivals Midjourney
  • Excellent prompt adherence
  • Self-hostable
  • Runs entirely locally, so there are no per-image fees or content-policy filters imposed by a hosted API.
  • Supports nearly every Stable Diffusion checkpoint, LoRA, VAE, and embedding format the community produces.
  • Massive extension ecosystem (ControlNet, Regional Prompter, Dynamic Prompts, ADetailer, etc.) covers advanced workflows.
  • Fine-grained control over samplers, CFG, seeds, prompt weighting, and prompt scheduling that hosted tools rarely expose.
  • Built-in training paths for textual inversion, hypernetworks, and LoRA on your own datasets.
  • Works on modest hardware (reports of usable output at 4GB VRAM with low-precision modes) and supports Apple Silicon.
Cons
  • [pro] is API-only
  • Self-hosting needs serious GPU
  • Setup requires Python 3.10, Git, and matching GPU drivers, which is a real barrier for non-technical users.
  • The Gradio UI is dense and inconsistent; discoverability of features is poor compared to newer node-based tools like ComfyUI.
  • Development cadence has slowed and it lags behind ComfyUI on newer model architectures (SDXL refinements, SD3, Flux support arrives late or via extensions).
  • No first-party hosted version — you are responsible for GPU cost, updates, and extension conflicts.
  • Extension quality varies wildly and a bad extension can break the whole install until you disable it.
Websiteblackforestlabs.aigithub.com
Pick Flux if
  • Open weights for [schnell]/[dev] variants
  • Quality rivals Midjourney
  • Excellent prompt adherence
  • Self-hostable
Pick Stable Diffusion Web UI (AUTOMATIC1111) if
  • Runs entirely locally, so there are no per-image fees or content-policy filters imposed by a hosted API.
  • Supports nearly every Stable Diffusion checkpoint, LoRA, VAE, and embedding format the community produces.
  • Massive extension ecosystem (ControlNet, Regional Prompter, Dynamic Prompts, ADetailer, etc.) covers advanced workflows.
  • Fine-grained control over samplers, CFG, seeds, prompt weighting, and prompt scheduling that hosted tools rarely expose.