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AI & Generation

What is CFG scale?

Also known as: Classifier-free guidance, Guidance scale

Classifier-free guidance scale — a parameter controlling how strictly a diffusion model follows the text prompt. Higher values produce more literal interpretations; lower values allow more creative variation.

In detail

CFG scale is the control parameter in classifier-free guidance, a technique that improves prompt adherence in diffusion models. The model generates two predictions at each denoising step — one conditioned on the prompt, one unconditioned — and CFG scale determines how strongly the conditioned prediction overrides the unconditioned. CFG 1.0 ignores the prompt entirely (produces unconditioned random outputs); CFG 7-8 is the typical default for balanced prompt-fidelity and creative variation; CFG 12+ produces strong prompt adherence but can over-saturate colors and reduce quality; CFG 3-5 allows creative drift away from the prompt. For textile work, CFG 5-8 is the sweet spot — prompts produce recognizable results but the AI has enough freedom to produce visually appealing compositions. Pushing CFG too high produces 'fried' outputs with unnatural saturation and contrast. A common pitfall: too high a CFG (12+) produces 'fried' or oversaturated output where the model over-commits to literal prompt interpretation, washing out fine detail. Too low a CFG (1-3) produces output that ignores the prompt almost entirely. Most textile workflows settle on CFG 6-8 as the productive zone.

Example

Prompt: 'soft watercolor peony floral, dusty pink and sage.' At CFG 7, the model produces a balanced soft watercolor look. At CFG 12, it produces an over-saturated, hyper-pink result with cartoonish edges. At CFG 4, it drifts toward generic florals that ignore the watercolor and color cues.

Related terms

Diffusion model
A class of generative AI models that produce images by iteratively denoising random Gaussian noise into coherent imagery. The dominant architecture for AI image generation in 2026, including textile pattern AI.
Stable Diffusion XL
Stability AI's open-source 2.6 billion parameter diffusion model released July 2023. The dominant model for textile pattern AI as of 2026, used by most production textile-AI platforms.
FLUX
Black Forest Labs' 12 billion parameter diffusion model released August 2024. Produces higher-fidelity generations than SDXL at higher GPU cost. Used by textile AI platforms for high-detail generation.
Seed value
An integer that initializes the random number generator a diffusion model uses to start generation. The same seed + same prompt + same model produces the same output exactly.

Go deeper

  • AI pattern generation guide