600+ AI Image Tests: OpenAI = Creative, Gemini = Realistic, Seedream = Fast

LateNiteSoft compared OpenAI, Gemini, and Seedream across 600+ real-world image edits, measuring quality, behavior, and speed. OpenAI is strongest for creative, transformative tasks; Gemini is best for faithful, realistic edits; Seedream is fast and often solid, with standout styles like low-poly and ukiyo‑e. They built a credit-based billing system and are prototyping a prompt classifier to auto-select models by edit type.

Key Points

• They tested 600+ generations across OpenAI gpt-image-1, Gemini 2.5 Flash Image, and Seedream 4-0-250828 using simple prompts on common photo subjects.
• Generation speed: OpenAI High ~80s (Medium ~36s), Gemini ~11s, Seedream ~9s; speeds were consistent across prompts and images.
• Gemini best preserves realism and reduces hallucinations but can be overly conservative or refuse edits, especially with human subjects.
• OpenAI excels at creative, fully transformative edits and style transfer but often re-synthesizes details, making it weak for precise tasks like background removal.
• Seedream is a fast, cost-effective middle ground with standout results in certain styles (e.g., ukiyo‑e, low poly, bokeh) but variable consistency.

Sentiment

The community broadly agrees with the article's findings, with most commenters confirming similar experiences from their own extensive testing. The discussion is constructive and adds meaningful technical depth, particularly around OpenAI's architectural limitations and Gemini's editing conservatism. Some pushback comes from advocates of local models who feel commercial API comparisons miss the bigger picture, and from a minority who think the methodology is flawed.

In Agreement

• Multiple users with extensive generation experience confirm each model has distinct strengths matching the article's conclusions
• Users validate that OpenAI excels at creative/transformative edits but hallucinates details and alters faces
• Gemini's conservatism and tendency to return images unchanged, especially with people, is widely confirmed
• Seedream is recognized as a strong middle-ground option, particularly for higher-resolution output and bokeh effects
• The article's routing strategy (artistic prompts to OpenAI, realistic prompts to Gemini) is endorsed by the community

Opposed

• Using generative AI for image filters is fundamentally misguided since traditional filters guarantee object preservation while AI guarantees nothing
• Local models with ComfyUI and LoRAs already outperform commercial API offerings for many specialized tasks
• The testing methodology is questioned — comparison across a limited set of prompts may not generalize and trial-and-error doesn't produce repeatable insights
• One photographer/artist strongly preferred OpenAI across the board, disagreeing with the article's nuanced each-has-strengths conclusion
• The article's choice of test images (especially the low-contrast mountain) may have produced misleadingly poor results