Comparing GPT Image 2.5 and Open-Source Image Generation Models

A comparative analysis of image generation shows that GPT Image 2.5 outperforms open-source models in understanding complex prompts.

Request Processing Features

Unlike other solutions tested in ComfyUI on Google Colab with an A100 GPU, GPT Image does not require adaptation to its specific features. The model can transform generalized and imprecise text descriptions into high-quality images without additional instructions.

Testing focused on rendering quality and detail adherence rather than censorship. For example, when processing a prompt describing pose and lighting, the model correctly interpreted complex compositional elements.

Automated Post-Processing

For mass image generation, there is a way to automatically add captions. Using ChatGPT, you can obtain a Python and FFmpeg script that analyzes file names and overlays watermarks indicating the model used.

This approach allows for quickly preparing an archive of numbered or marked images without manually analyzing their content.