I spent 2 days properly testing GPT Image 2.0, findings were more interesting than expected

I tested GPT Image 2.0 (released April 21) and wanted to write up actual observations instead of just reposting the OpenAI promo shots.

The text rendering improvement is the real story here. Generated a product spec sheet, a water cycle educational diagram with labeled arrows, and a poster layout with multilingual text. All came back readable, correctly spelled, properly placed. This is a genuine step change from 1.5 which would garble text at this density. Still has an edge case where it abbreviates words if you overcrowd the layout, but for most use cases it's solved.

Prompt I used:

"product spec sheet, wireless speaker, feature icons with labels, two-column layout, white background, minimal sans-serif"

Output

The image to image side surprised me more. Fed it a flat product photo with plain studio lighting and described adding window light from one direction. Shadow landed on the correct side, product shape didn't warp. Did the same with a hand-drawn room sketch rendered to a styled interior and spatial understanding held up well.

Output of Image to Image Testing

Portrait accuracy is also genuinely better than 1.5. Not in a Midjourney stylistic sense, those two have a very different visual character, but for following a specific prompt description of a face, expression or lighting setup, instruction adherence is strong. Ran a side by side with Flux on the same portrait prompt and GPT Image 2 was more literal in hitting the description.

For multi-model comparison I was using Vosu AI, has gpt-image-2 alongside Flux and a few others so I could run the same prompt through multiple models without switching between tools. Helpful specifically for the portrait and image-to-image comparison tests.

DALL-E 2 and DALL-E 3 are being deprecated May 12 if anyone is still building on those.