Sampling Steps Parameters

The number of denoising iterations during image generation. More steps generally produce higher quality but take longer to generate.

Sampling steps (or just “steps”) control how many times the model refines the image during generation.

How Steps Work

  1. Generation starts with random noise
  2. Each step removes some noise
  3. More steps = more refinement opportunities
  4. Eventually, quality plateaus
StepsResultUse Case
10-15Quick draftsPreviewing compositions
20-30Good qualityGeneral use
30-50High qualityFinal renders
50+Diminishing returnsUsually unnecessary

Sampler Matters

Different samplers need different step counts:

  • Euler, DPM++ 2M: Good at 20-25 steps
  • DPM++ SDE: Benefits from 30+ steps
  • DDIM: Stable across step counts
  • Ancestral samplers: Never fully converge

Quality vs Speed

More steps mean:

  • Better detail refinement
  • Smoother gradients
  • Longer generation time
  • Eventually no improvement

Tips

  • Start with 20-25 steps for most work
  • Use fewer steps when iterating on prompts
  • Increase for final high-quality renders
  • Watch for when quality stops improving
  • Some models are optimized for fewer steps