What is the difference between ancestral and non-ancestral samplers?

Ancestral samplers (names ending in 'a', like Euler a) inject noise at each step, so the image keeps changing and never fully converges. Non-ancestral samplers (Euler, DPM++ 2M, DDIM) converge to a stable result as steps increase, which is better for reproducibility and upscaling.

What is the safest all-round sampler?

DPM++ 2M Karras is the common default — it gives sharp, coherent results in 20–30 steps and converges cleanly, which makes it reliable for both first passes and hires fix.

Why does the same seed look different on another sampler?

Each sampler integrates the denoising path differently, so the same seed and prompt produce a different image per sampler. Lock the sampler along with the seed when you need reproducibility.

Is anything sent to a server?

No. This is a static reference that runs in your browser. Nothing is uploaded, generated or logged.

SD Sampler Selector Guide

Stable Diffusion sampler selector guide

The sampler decides how Stable Diffusion turns noise into your image, and the right choice changes both speed and look. Tell this guide whether you want speed, quality or consistency, and it recommends a sampler with a sensible step range — backed by a full comparison table.

How samplers differ

A sampler is the numerical solver that walks the image from pure noise toward the denoised result. They fall into two broad families:

Ancestral / stochastic (Euler a, DPM++ 2S a) inject fresh noise each step. They produce lively, varied output but never fully converge — adding steps keeps changing the image.
Convergent (Euler, DPM++ 2M Karras, DDIM, UniPC) settle toward a stable result. These are best for reproducibility, hires fix and upscaling, because more steps refine rather than redraw.

The Karras label refers to a noise schedule that spends more steps where they matter most, which is why DPM++ 2M Karras reaches clean results in relatively few steps.

Tips for choosing

Need it fast? Euler a or DPM++ 2M Karras look good by ~20 steps.
Need the best detail? DPM++ 2M Karras or DPM++ 3M SDE at 25–35 steps.
Need it reproducible? Pick a convergent sampler (DDIM, Euler) and lock the seed.
Test, don’t trust. Generate the same prompt across three samplers at a fixed seed and pick the look you prefer — that beats any chart.