How It Works

AI Image & Video Generation: Optimal Width, Height & Aspect Ratios

Master the optimal dimensions and aspect ratios for every AI image generation model

Shawn @ Prompting Pixels

What You'll Learn

Learn the optimal width, height, and aspect ratio settings for AI image models including Stable Diffusion, SDXL, and Flux Dev. Includes comprehensive dimension tables and best practices.

Video Walkthrough

Prefer watching to reading? Follow along with a step-by-step video guide.

Width & Height

When generating images with AI models like Stable Diffusion, Flux, and other image generation models, the width and height parameters are crucial settings that significantly affect your final result.

Width and height determine both the size and aspect ratio of your generated image. Each AI model has an optimal range of dimensions where it performs best, based on the resolution it was trained on.

Quick Reference Tool

For pixel-perfect dimensions optimized for any AI model, use our AI Image Aspect Ratio Calculator. It provides one-click copying of dimensions in multiple formats with real-time megapixel calculation and constraint validation.

Optimal Dimensions by Model

Stable Diffusion Models

  • Stable Diffusion 1.5: 512x512 pixels (1:1 aspect ratio) - trained on 512px resolution

  • Stable Diffusion 2.1: 768x768 pixels (1:1) - trained on 768px resolution

  • Stable Diffusion XL (SDXL): 1024x1024 pixels (1:1) - trained on 1024px resolution with 15+ officially supported aspect ratios

  • SDXL Turbo: 512x512 pixels - optimized for speed at lower resolution

  • SDXL Lightning: 1024x1024 pixels - same as SDXL base

  • Pony Diffusion: 1024x1024 pixels (SDXL-based)

Modern AI Image Models

  • Flux Dev: Flexible megapixel targeting with 32px increment constraints (typically 1024x1024 or 1 megapixel equivalents)

  • Flux Schnell: Same as Flux Dev, optimized for speed

  • Hunyuan DiT: 1024x1024 pixels recommended

  • Qwen VL (Image): Flexible dimensions, typically 1024x1024 or higher for best quality

  • Kolors: 1024x1024 pixels (similar to SDXL)

SDXL Supported Aspect Ratios

SDXL natively supports these resolutions for optimal quality:

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Width x Height Aspect Ratio Use Case

1024 x 10241:1 (square)Social media, icons 1152 x 8969:7Portrait orientation 896 x 11527:9Portrait orientation 1216 x 83219:13Landscape photos 832 x 121613:19Portrait photos 1344 x 7687:4Wide landscape 768 x 13444:7Tall portrait 1536 x 64012:5Ultra-wide 640 x 15365:12Ultra-tall

Flux Dev Recommended Dimensions

Flux Dev works with dynamic megapixel targeting and requires dimensions in 32px increments:

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Width x Height Aspect Ratio Megapixels

1024 x 10241:11.0 MP 1344 x 76816:91.0 MP 768 x 13449:161.0 MP 1216 x 8323:21.0 MP 832 x 12162:31.0 MP 1536 x 10243:21.6 MP 1024 x 15362:3~1.6 MP

Legacy Models

For older Stable Diffusion models, here are the recommended dimensions:

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Width x Height Aspect Ratio SD 1.5 SD 2.1

512 x 5121:1 (square)✓– 768 x 5123:2✓– 512 x 7682:3✓– 768 x 5764:3✓– 896 x 51216:9✓– 768 x 7681:1 (square)–✓ 1152 x 7683:2–✓ 768 x 11522:3–✓ 1024 x 7684:3–✓ 1152 x 64816:9–✓

Best Practices

  • Stay close to training resolution: Each model performs best at or near its native training resolution

  • Respect minimum dimensions: Never go below the minimum edge length the model was trained on (512px for SD 1.5, 768px for SD 2.1, 1024px for SDXL/Flux)

  • Use proper constraints: Many models require dimensions divisible by 8, 32, or 64 pixels

  • Consider megapixels: Higher megapixel values mean slower inference. Lower resolutions generate faster

  • Match aspect ratio to content: Use portrait ratios for people, landscape for scenery, square for social media

  • Use the calculator: Visit aspect.promptingpixels.com for pixel-perfect dimensions that avoid generation errors

Impact on Quality

Different aspect ratios and dimensions can significantly influence the final output quality:

  • Images generated at non-native resolutions may show artifacts or reduced quality

  • Extreme aspect ratios (like 16:9) work better with SDXL and Flux than older models

  • Upscaling from native resolution often produces better results than generating at high resolution directly

  • Composition and framing can be affected by aspect ratio choice

Video Generation Models

Note: Some AI models like Wan 2.2 are designed for video generation (text-to-video and image-to-video) rather than static image generation. These models have different resolution requirements:

  • Wan 2.2 T2V: Supports 480P and 720P video generation at 24fps. Generates 5-second videos using resolutions like 1280x720 (720P) or 854x480 (480P)

For the most reliable results across any AI image generation model, use our AI Image Aspect Ratio Calculator to ensure your dimensions are optimized for your chosen model.

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