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FLUX Comparison SCHNELL vs DEV IMAGE TO IMAGE TEXT TO IMAGE INPAINTING

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Introduction

In this article, we will explore the differences between two versions of the FLUX model: the FLUX Dev version and the FLUX Schnell version. We will discuss their differences in understanding prompts, image quality, and even inpainting capabilities. By the end, readers will have a holistic understanding of these two models and how they fare in various tasks, including generating images with different facial expressions.

Model Updates and Installation

Recent updates have allowed users to download these models at half of their original size, making them more accessible for computers with limited RAM. To use these models, download them and place them in the model/unet folder. If you have previously installed the earlier version of FLUX, you only need to download the new models. The T5X XL and VA models remain unchanged from the previous version.

It is crucial to note that FLUX Dev is not intended for commercial use, which should be considered when choosing between these models. Additionally, FLUX Dev is tuned to 20 steps, whereas FLUX Schnell is set to 4 steps. For this comparison, we kept all settings identical, except for the model type and the number of steps used.

Image Generation Comparison

As we dive into the text-to-image comparison, the differences between the two models become apparent.

  • Image Examples: We compared images generated from the same prompt using both models. The FLUX Schnell version is displayed on the left, while the FLUX Dev version is on the right. Many of the images from the Dev model exhibit more dramatic and interesting effects, which could be a matter of personal taste.

  • Detail and Quality: The quality differences are astonishing, particularly in portraits where FLUX Dev tends to achieve a more photographic look. The prompt consistency resulted in almost identical characters in both models, but FLUX Dev's images felt more realistic and closer to photography.

  • Text Association: When examining a prompt related to a food stall with signage, FLUX Schnell managed to reference the text, but FLUX Dev contextualized it more logically, showcasing a better understanding of the prompt.

Resolution and Quality

Resolution plays a significant role in the quality of generated images. For example, a resolution of 1216x1216 resulted in a blurry image, while adjusting to 1024x1024 significantly improved the output. This trend of resolution affecting the outcome is valid for both models.

Image-to-Image Comparison

The differences persist when comparing the image-to-image capabilities. In image transitions, FLUX Dev offers more freedom and the denoise functionality operates differently with fewer steps, yielding diverse results. Furthermore, FLUX Dev generally produces images that exude more realism compared to FLUX Schnell.

Inpainting Capabilities

Inpainting, or altering specific portions of an image while keeping the rest intact, saw significant improvements in FLUX Dev. Attempts to use inpainting with FLUX Schnell were largely unsuccessful, while FLUX Dev managed to achieve results that seamlessly integrated changes. For example, using a mask to prompt a smile on a face yielded a harmonized output.

Character Consistency and Expression Changes

In summary, FLUX Dev's understanding of prompts allows for consistent portrayal of characters with varying expressions. A detailed prompt was created by utilizing GPT to offer different moods while maintaining the same character, and the FLUX Dev model succeeded in generating varying facial expressions effectively.

Conclusion

The FLUX Dev model offers notable improvements in understanding prompts, image quality, and inpainting over FLUX Schnell. For tasks involving detailed character expression variations and higher-quality visual outputs, FLUX Dev proves to be more efficient and effective.


Keywords

  • FLUX Dev
  • FLUX Schnell
  • Image generation
  • Text-to-image
  • Inpainting
  • Prompt understanding
  • Image quality
  • Character expressions
  • Denoise function

FAQ

  1. What is the primary difference between FLUX Dev and FLUX Schnell?

    • FLUX Dev has better understanding of prompts, higher image quality, especially in realism, and superior inpainting capabilities compared to FLUX Schnell.
  2. Can FLUX Dev be used for commercial purposes?

    • No, FLUX Dev is not intended for commercial use.
  3. How do the image resolutions affect the outputs in both models?

    • Higher resolutions can yield clearer images, while incorrect ratios can result in blurriness. Both models are impacted by resolution settings.
  4. What improvement does FLUX Dev offer in inpainting?

    • FLUX Dev produces more coherent and aesthetically pleasing results in inpainting tasks compared to FLUX Schnell, achieving seamless image modifications.
  5. Are the character outputs consistent between different prompts in FLUX Dev?

    • Yes, FLUX Dev maintains character consistency even with varying facial expressions and moods as dictated by the changes in prompts.
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