Botmonster Tech
ControlNet lets you steer Stable Diffusion with spatial inputs: hand-drawn sketches, Canny edge maps, depth images, or OpenPose skeletons. The output then follows your layout, not your prompt alone. You feed a control image next to your text prompt. The model builds artwork that matches the structure of your input. It then fills in texture, lighting, and detail from the prompt. You get pixel-level control that no prompt tweak can match.
Stable-Diffusion
Run FLUX 2 Locally in 2026: VRAM by GPU + ComfyUI Setup
You can run FLUX 2 locally on a single consumer GPU in 2026. The open-weight FLUX 2 dev is a 32B model from Black Forest Labs that fits a 24GB card when quantized, while the smaller Klein builds run on 8GB. This guide picks the right variant for your card, installs it in ComfyUI, and covers what it costs to run.
Key Takeaways
- FLUX 2 dev needs a 24GB card; Klein runs on 8GB.
- ComfyUI plus Stability Matrix is the fastest way to start.
- Quantized GGUF builds cut VRAM in half with little quality loss.
- Running locally costs a fraction of a cent per image in power.
- Only dev and Klein have downloadable weights; Pro and Max are API only.
SDXL 2.0 LoRA: 50-300 MB Adapters on 12 GB VRAM
The best way to fine-tune Stable Diffusion XL 2.0 is with Low-Rank Adaptation (LoRA) : a small adapter that injects your style or subject without touching the base weights. Instead of retraining the full model, LoRA trains a tiny side network next to the frozen base. The result is a 50 to 300 MB file you can load, swap, and stack at inference, trained on a 12 GB GPU in an afternoon.