AI Image Resolution Calculator for SDXL, FLUX and DALL-E

Pick an aspect ratio and get the native generation size for SDXL, SD 1.5, FLUX.1, SD 3.5, DALL-E 3 and gpt-image-1, plus the Midjourney --ar value, how far each is off your ratio and the upscale needed for your final size.

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Results will appear here once you enter your values.

How the calculator works

Choose a preset such as 16:9, 4:5 or 21:9, or type any width and height. Pixel sizes work too: 1920 and 1080 reduce to 16:9. The tool then applies each model's sizing rule and shows the resulting size, megapixels, how far that size is from your ratio, and the size after your chosen upscale factor (1x, 1.5x, 2x, 3x or 4x).

  • SDXL 1.0: the nearest of nine roughly 1 MP buckets, from 1024x1024 through 1344x768 and 1536x640, plus their portrait versions.
  • Stable Diffusion 1.5: short side 512, long side a multiple of 64, capped at 1024.
  • FLUX.1 dev and schnell: your chosen area (0.5, 1, 1.5 or 2 MP) with both sides rounded to a multiple of 16.
  • Stable Diffusion 3.5: about 1 MP with sides divisible by 64.
  • DALL-E 3 and gpt-image-1: the closest of their three fixed sizes.
  • Midjourney: the reduced --ar value, with an approximate pixel size.

Why native resolution matters

Diffusion models learn composition at a specific pixel count. SDXL was trained on multiple aspect ratios at about one megapixel, and SD 1.5 at 512x512, so asking SD 1.5 for 1920x1080 directly often produces duplicated heads, extra limbs and repeated objects. The reliable workflow is to generate at the native size and then upscale.

For a 16:9 target the calculator returns 1344x768 for SDXL and SD 3.5, 896x512 for SD 1.5, 1328x752 for FLUX.1 at 1 MP, 1792x1024 for DALL-E 3, and --ar 16:9 for Midjourney. The first four are 1.56% or less off a true 16:9. gpt-image-1 has no wide option, so its closest size, 1536x1024, is 15.6% off and needs a crop.

Enter a target output such as 3840x2160 and the tool shows the factor each model needs to cover it. SDXL at 1344x768 needs 2.86x, and anything above 4x is flagged so you can split it into two upscale passes.

Common mistakes

Ignoring the aspect error. When the aspect column goes above 5%, the model's allowed size does not match your ratio and you will need to crop. A 3:2 request is exact for gpt-image-1 at 1536x1024, but DALL-E 3's nearest size, 1792x1024, is 16.7% wider.

Using odd dimensions. The diffusers FLUX pipeline expects height and width divisible by 16 and warns otherwise, and SD models are built around multiples of 8 or 64. Arbitrary sizes like 1000x563 get resized or rejected.

Typing decimals into Midjourney. The --ar parameter only takes whole numbers, so 1.85:1 has to become 37:20. The calculator reduces any ratio you enter to whole numbers for you, and its pixel estimate is marked approximate because Midjourney picks the exact size.

Tips for better results

Use the megapixel picker for FLUX.1 deliberately. One megapixel is the safe default, while 1.5 or 2 MP gives more detail at the cost of generation time and a higher chance of composition errors.

  • Fine-tunes such as Pony and Illustrious inherit SDXL's buckets, so use the SDXL row for them.
  • For print or 4K, generate at the native size, upscale 2x, then crop the small aspect difference.
  • Stability AI describes SD 3.5 Large as a 1 megapixel model and SD 3.5 Medium as working between 0.25 and 2 MP, so stay near 1 MP for Large.
  • Newer GPT image models accept custom sizes, but gpt-image-1 and DALL-E 3 only take the three sizes listed in this table.

Frequently Asked Questions

Common questions about the AI Image Resolution Calculator for SDXL, FLUX and DALL-E

Use 1344x768. It is one of the nine roughly one megapixel buckets used for SDXL, and its ratio of 1.75 is only 1.56% narrower than a true 16:9. Generate at that size, upscale 2x to 2688x1536, then crop or resize to 2560x1440. For portrait 9:16 content such as Reels or TikTok, use the mirrored 768x1344 bucket.
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Sources & References

Podell et al. (2023), SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis, arXiv:2307.01952

SDXL multi-aspect training at ~1 megapixel.
→Source: arXiv

Hugging Face diffusers: FLUX pipeline source (height and width divisibility check)

FLUX pipeline requires height and width divisible by 16.
→Source: Hugging Face (diffusers)

Stability AI: Introducing Stable Diffusion 3.5

SD 3.5 Large/Medium resolution ranges.
→Source: Stability AI

OpenAI Cookbook: What's new with DALL-E 3

DALL-E 3 supported sizes 1024x1024, 1792x1024, 1024x1792.
→Source: OpenAI

OpenAI Cookbook: Generate images with GPT Image

gpt-image-1 supported sizes 1024x1024, 1536x1024, 1024x1536.
→Source: OpenAI

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