Slides: You Might Not Need 50 Diffusion Steps — Ziv Ilan, Nvidia

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You Might Not Need 50 Diffusion Steps — Ziv Ilan, Nvidia

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Extracted Slides

OCR text:

nVIDIA

You Might Not Need

50 Diffusion Steps

AlEngineer

EURORE

OCR text:

Diffusion models: What & Why

+ Generate mages/video by iteratrvely denoising from random nase

- Each step: neural network predicts and removes nose — refines output

a *& + Quality comes from many refinement passes {typically 20-50 steps)

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+ Powering today’s leading models

bal x + FLUX 2 (Black Forest Labs} — SOTA text-to-image, photoreakstic

* bd of + LTX-2 3 (Laghtsicks) — 22B params, 4K@SOfps video + audro

+ Wan 2.7, HunyuanVideo. Seedance 20.

- Used for: text-to-image, text-to-video, image editing, 3D generation, inpainting, super-resolution, world simulation,

scientific modeling

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Quantization: Performance & Quality

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