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Adaptive Step Samplers improve ComfyUI image generation

A new open-source project called Adaptive Step Samplers has been released, offering an improved method for image generation in diffusion models. This project modifies the SA-Solver within ComfyUI to allow for adjustable stochastic strength (eta), addressing limitations of existing samplers like Euler and ancestral samplers. The SA-Solver, originally from Xue et al. (NeurIPS 2023), now offers better texture and anatomy preservation at low step counts, providing a superior alternative for image generation. AI

IMPACT Enhances image generation quality and flexibility in diffusion models by improving sampler performance.

RANK_REASON This is a modification and improvement to an existing tool (ComfyUI) and a specific algorithm (SA-Solver), rather than a novel release from a frontier lab or a significant industry-wide event.

Read on r/StableDiffusion →

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Adaptive Step Samplers improve ComfyUI image generation

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This is a modification and improvement to an existing tool (ComfyUI) and a specific algorithm (SA-Solver), rather than a novel release from a frontier lab or a significant industry-wide event.
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COVERAGE [1]

  1. r/StableDiffusion TIER_2 English(EN) · /u/YakovSava ·

    [Resource] We unlocked SA-Solver in ComfyUI: why stochastic strength eta=1.7 beats Euler at 10 steps (and what didn't work)

    <!-- SC_OFF --><div class="md"><p>Hey everyone,</p> <p>If you generate images on modern diffusion and flow-matching models (Flux, SD3, Anima) at low step counts (8–14 steps), you're probably stuck between two bad options:</p> <ul> <li><strong>Euler:</strong> Good macro anatomy, b…