Section 10.5.3 : Stable Diffusion, Flux, and open-source AI
🎯 Learning objective
Understand the open-source image generation ecosystem — Stable Diffusion, Flux, and their variants — for total control, advanced customization, and unrestricted usage. You'll know when and why to choose open-source, how to get started without a powerful GPU, and how to leverage advanced features (ControlNet, LoRA, inpainting).
Why open-source is a game-changer
Proprietary models (DALL-E, Midjourney) are simple but limited: content censorship, no fine-tuning possible, cloud dependency, recurring monthly cost. Open-source models offer a fundamentally different alternative:
| Aspect | Proprietary (DALL-E, MJ) | Open-source (SD, Flux) |
|---|---|---|
| Content control | Imposed filters and restrictions | No technical restrictions |
| Customization | None | Fine-tuning, LoRA, embeddings |
| Privacy | Data sent to cloud | 100% local, no external data |
| Recurring cost | $10-60/month | $0 (after GPU purchase) |
| Reproducibility | Limited (seeds not guaranteed) | Total (seed + model = same result) |
| Speed | Depends on server | Depends on your GPU (often faster) |
| Learning curve | Easy | Medium to difficult |
| Community | Official forums | Massive, thousands of models on Civitai/HuggingFace |
Key open-source models in 2026
| Model | Developer | Main strength | Recommended GPU | Model size |
|---|---|---|---|---|
| Stable Diffusion 3.5 Large | Stability AI | Versatile, huge community, thousands of extensions | 8 GB VRAM | 8.1 GB |
| Stable Diffusion 3.5 Medium | Stability AI | Good quality/speed tradeoff for modest GPUs | 6 GB VRAM | 4.6 GB |
| Flux.1 Dev | Black Forest Labs | State-of-the-art photorealistic quality, Midjourney rival | 12 GB VRAM | 23 GB |
| Flux 1.1 Pro | Black Forest Labs | Best quality (cloud API) | Cloud API | - |
| SDXL | Stability AI | Most compatible, most LoRAs available | 8 GB VRAM | 6.9 GB |
Which one to choose to start?
- →6-8 GB GPU (RTX 3060, RTX 4060): start with SD 3.5 Medium or SDXL
- →12+ GB GPU (RTX 4070, RTX 4080): go directly to Flux.1 Dev
- →No GPU: use cloud platforms (see below)
Interfaces: how to use the models
Open-source models aren't used alone — you need an interface:
ComfyUI (recommended for advanced users):
- →Node-based interface (like Blender or Unreal Engine): each pipeline step is a node you connect
- →Total and granular control over EVERY generation step
- →Reusable and shareable workflows (JSON files)
- →Massive community of custom nodes (2000+ extensions)
- →Installation:
git clone→ Python → launchmain.py - →Key advantage: complex workflows (inpainting + ControlNet + upscale in a single pipeline)
Automatic1111 WebUI / Forge (recommended for beginners):
- →Simple and intuitive web interface (browser)
- →1-click installation with launchers (Easy Diffusion, Pinokio)
- →The most popular interface (most tutorials use a1111)
- →Extensions: ControlNet, ADetailer, Ultimate SD Upscale, etc.
- →Forge is an optimized fork of a1111, faster and lighter on VRAM
- →Key advantage: ease of use, extensive documentation
Fooocus (the simplest):
- →Minimalist interface, inspired by Midjourney
- →Simple prompts → high quality without any technical tweaking
- →1-click installation
- →Based on SDXL with optimized presets
- →Key advantage: pro results in 2 minutes, no understanding of internals needed
Advanced open-source features
ControlNet: composition control (the killer feature)
ControlNet lets you precisely control the composition and pose of your images, something no proprietary tool does as well:
| Control type | Input | Result | Use case |
|---|---|---|---|
| Canny Edge | Image → edge extraction | AI generates following the edges | Reproduce an existing composition |
| Depth Map | Image → depth map | AI respects the 3D depth of the scene | Architectural scenes, landscapes |
| OpenPose | Photo of a person → skeleton | AI generates a character in the same pose | Fashion, consistent characters |
| Scribble | Quick hand sketch | AI transforms the sketch into a pro image | Rapid visual prototyping |
| Tile | Low resolution image | AI adds details (intelligent upscale) | Improve existing photos |
| IP-Adapter | Reference image | AI copies the style/subject of the reference | Brand consistency |
Concrete example: you draw a rough sketch (5 minutes) of your illustration's composition with Scribble, and the AI produces a professional image that respects exactly your layout. It's like having an instant illustrator who follows your visual instructions.
LoRA (Low-Rank Adaptation): accessible fine-tuning
A LoRA is a small file (50-200 MB) that modifies a model's behavior for a specific style or subject:
- →Style LoRA: "anime style", "fashion photography", "children's illustration"
- →Concept LoRA: "your logo", "your product", "a specific building type"
- →Character LoRA: trained on 20-50 photos of a person → the model can generate that person in any context
Where to find LoRAs: civitai.com (the largest library, 100K+ LoRAs)
Create your own LoRA: possible with 20-50 training images and ~30 minutes of compute on a 12GB GPU. Tools like Kohya_ss simplify the process.
Inpainting: modify specific areas
Select an area of the image → describe what you want instead → the AI regenerates ONLY that area, naturally blending with the rest. Ideal for: correcting a detail, changing an object, replacing a background.
Cloud platforms (no GPU needed)
If you don't have a powerful GPU, several options exist:
| Platform | Price | Available GPU | Interface |
|---|---|---|---|
| Civitai | Free (limited) → $10/month | Variable | Web (simple) |
| RunPod | ~$0.30/h (RTX 4090) | RTX A5000, A6000, 4090 | ComfyUI/a1111 pre-installed |
| Vast.ai | ~$0.20/h (variable) | Variable (marketplace) | SSH + your interface |
| Google Colab | Free (limited) → $10/month | T4, A100 | Python Notebook |
| Replicate | ~$0.01/image | Serverless | API + web |
My recommendation for getting started without a GPU
- →Test for free: Civitai.com → try SDXL and Flux online, no installation needed
- →If you like it: install Fooocus on Google Colab (free, zero config)
- →If you want more control: rent a GPU on RunPod ($0.30/h) with pre-installed ComfyUI
- →If you're convinced: invest in a 12GB+ GPU (RTX 4070: ~$550) for unlimited local generation
What is the main advantage of open-source models (Stable Diffusion, Flux) over DALL-E and Midjourney?
What does ControlNet allow you to do in Stable Diffusion?