Imagen 3: Google takes on Flux?

🌈 Abstract

The article compares the performance of two text-to-image AI models - Flux (developed by Black Forest Labs) and Imagen-3 (developed by Google). The author conducts a series of tests using various prompts and evaluates the quality and accuracy of the generated images from both models.

🙋 Q&A

[01] Comparing Flux and Imagen-3

1. What are the key findings from the author's comparison of Flux and Imagen-3?

• The author concludes that Flux has an edge over Imagen-3 in terms of image quality and adherence to the prompts, though the difference is not massive.
• Flux's images are generally better than Imagen-3's, but Imagen-3 is still a fantastic text-to-image model, better than DALL-E 3.
• Both models perform well on text rendering, but Imagen-3 is more heavily censored and sometimes fails to generate images for certain prompts.

2. How did the author access and test Imagen-3?

• The author had to use a VPN (NordVPN) to access Imagen-3, as it was not available in their country (the UK).
• They then followed the steps to access Imagen-3 through the ImageFX website, which involved signing in with a Google account.

3. What were the key differences in the capabilities of the two models?

• Flux only generated one image per prompt, while Imagen-3 generated up to 4 images per prompt.
• In terms of speed, the author found both models to be equally responsive.
• Imagen-3 was more heavily censored and failed to generate images for certain prompts, like a fight between Superman and Spiderman.

[02] Prompts and Image Comparisons

1. What were the key prompts used to compare Flux and Imagen-3?

• A superhero like the Flash running across the ocean at super speed
• A hippo riding a bicycle
• A scene with a blue ball, red box, rainbow, pirate, and a plate of roast dinner
• A no parking sign with a $50 penalty
• A fight between Superman and Spiderman (which Imagen-3 could not generate)
• A hyper-realistic 8K image of a colorful bowl of fruit

2. How did the author evaluate the quality and accuracy of the generated images?

• The author subjectively assessed which model produced the best quality image that adhered most closely to the prompt.
• They compared the images side-by-side, with the Imagen-3 image always on the left.

3. What were the author's overall impressions of the two models' performance?

• The author concluded that Flux has a slight edge over Imagen-3 in terms of image quality and prompt adherence, though the difference is not massive.
• They felt Imagen-3 is a fantastic model, better than DALL-E 3, but Flux still comes out on top in their evaluation.