AI Image Models Tested

Product photography is undergoing a paradigm shift: away from the physical set, towards generative AI. But which model delivers the most professional results with the same inputs?

To find out, we used AMALYTIX to create precise prompts for seven typical e-commerce scenarios and seven products from Amazon’s catalog. These include Application Images, Infographic Images, Lifestyle Images, Macro Images, Rendering Images, Scale and Size Images, and Seasonal Gift Images.

These prompts were then tested on a range of modern AI image models. Our comparison includes: Flux.2 [Flex], Flux.2 Pro, Google’s models Gemini 2.5 Flash Image and Gemini 3 Pro, as well as GPT Image 1, GPT Image 1.5, and GPT Image 2 by OpenAI.

In this article, we compare the results and show which AI delivers the best product images.

Evaluation Criteria

For a structured and clear analysis of the AI models, we developed a detailed evaluation system. Each image is independently assessed by two experts from our marketing team based on three core criteria. A score from 1 (poor) to 5 (very good) is awarded in each category:

1. Overall Impression: This category assesses the visual impact, image composition, and overall quality of the result.

2. Realism: This evaluates the credibility and authenticity of the generated elements. Assessment criteria include natural proportions, correct object structures, and coherent lighting.

3. Prompt Accuracy: This category measures how precisely the instructions were followed. The decisive factor is the content’s consistency with the prompt.

The final overall score is then calculated as the average of all individual ratings.

Application Images

Select a product:

backpack

camera

flammschale

garlicpress

magnesium

microphone

rittersport

Application images show a product in a typical usage scenario. They help Amazon customers to imagine its use in everyday life and to better understand the practical benefits of the item.

This category showed clear performance differences. GPT Image 2 and Gemini 3 Pro delivered the strongest results in the existing test set. Compared to GPT Image 1.5, GPT Image 2 shows a clear step forward: product integration looks more natural, human-product interactions are less error-prone, and scenes are more coherent overall.

In contrast, the Flux models had visible difficulties with this task. Unnatural body postures, anatomical errors, or incorrect depictions of the product itself occurred more frequently. Flux 2 Pro also often interpreted the core of the prompt imprecisely, leading to irrelevant or unusable results.

Particularly detailed products like the backpack pushed the models to their limits. Likewise, the realistic representation of the fire bowl in the correct size and texture proved to be a challenging requirement.

Conclusion: Creating high-quality application images remains a complex challenge for AI models. In the updated comparison, GPT Image 2 takes the lead and shows clear progress over GPT Image 1.5. The other models in the existing results still show more frequent weaknesses in human-product interactions and precise product depiction.

Infographic Images

Select a product:

backpack

camera

flammschale

garlicpress

magnesium

microphone

rittersport

Infographics are intended to visually and concisely summarize product features. Through text, icons, and a clear structure, complex information is made easily understandable for customers.

With GPT Image 2, the infographic assessment shifts clearly. The model now delivers the strongest combination of readable text, visual structure, and semantic mapping. In the tested examples, text was almost consistently correct and clearly more reliable than with GPT Image 1.5.

The main improvement is not only cleaner text, but the relationship between text and product. Labels, icons, and connector lines are placed much more logically on actual product areas, making the layouts look less random and more like intentionally designed Amazon infographics.

A general limitation remains realism. GPT Image 2 is clearly stronger than GPT Image 1.5, but not fully consistent in every single example. Small text elements and product-critical details should still be checked manually. Flux.2 Pro still shows its known discrepancy: sometimes realistic visuals, but unreliable execution of the infographic task itself.

Conclusion: GPT Image 2 makes infographics much more practical for Amazon use cases. In our tests, text rendering was stable enough for many cases to become realistically usable. Manual review is still recommended, especially for small text, technical claims, and product-specific details.

Lifestyle Images

Select a product:

backpack

camera

flammschale

garlicpress

magnesium

microphone

rittersport

Lifestyle images show products in an appealing, everyday environment. They aim to build an emotional connection with the customer and convey the brand message by presenting the item in a relevant context.

Overall, this category was among the better-rated scenarios. The models showed a high accuracy in implementing the prompts and understood the desired scenarios. The biggest and most consistent weakness, however, was in realism. The depicted scenes often looked artificial and inauthentic.

In the updated comparison, GPT Image 2 ranks among the strongest models in this category and clearly outperforms earlier OpenAI models. Compositions look more polished and professional, and human-product interactions are less error-prone than with GPT Image 1.5. Gemini 3 Pro is also strong in the existing results.

The general weakness in realism was evident in the other models. GPT Image 1 stood out negatively here, with its images looking the most unnatural. The other models also had difficulties creating authentic and photorealistic scenes, even when the content of the prompt was correctly implemented.

Conclusion: Stronger models already handle lifestyle-image intent well. GPT Image 2 raises the level in composition and prompt execution, but photorealistic consistency remains the key challenge in individual outputs.

Macro Images

Select a product:

backpack

camera

flammschale

garlicpress

magnesium

microphone

rittersport

Macro images are extreme close-ups that highlight the finest product details, material texture, and quality features. They are crucial for demonstrating an item’s value and workmanship.

This scenario was one of the worst-rated in the entire test, revealing a key weakness of AI models: the realistic depiction of details. The generated close-ups consistently looked unnatural and artificial, which was reflected in the lowest realism score of all categories.

In this category as well, GPT Image 2 improves performance compared to GPT Image 1.5, but it does not fully solve the core problem. In strongly zoomed-in product areas, models still often lack context to render materials, textures, and exact product details correctly.

Significant realism issues remain visible across models. GPT Image 2 hallucinates less than earlier OpenAI models, but product consistency is still a critical checkpoint. GPT Image 1 remains particularly weak in this area.

Conclusion: Credible macro imagery remains one of the biggest hurdles for current AI models. GPT Image 2 improves outcomes, but material realism, detail fidelity, and product consistency still require strict manual review. Reference images and additional context remain essential.

Rendering Images

Select a product:

backpack

camera

flammschale

garlicpress

magnesium

microphone

rittersport

Renderings are computer-generated, photorealistic images of products. They are often used for studio shots with perfect lighting, displaying prototypes, or visualizing products in a neutral, controlled environment.

Similar to other technically demanding scenarios, creating convincing renderings was a major challenge for most AI models. While the prompts were generally understood, the results often lacked the crucial photorealism required for renderings.

In the updated comparison, GPT Image 2 is part of the top tier for rendering images as well. In many cases, it delivers stronger product depiction, better lighting logic, and more robust composition than GPT Image 1.5.

The other models—Flux.2 Pro, Flux.2 [Flex], and GPT Image 1—could not keep up. Their results suffered from a very low realism score, making them unusable for creating high-quality renderings. The generated images looked flat and artificial, and did not meet the expectations of a photorealistic representation.

Conclusion: High-quality renderings still clearly separate model quality. GPT Image 2 and the Gemini models are the most reliable options in this category, while Gemini 2.5 Flash Image remains a strong alternative for rendering-focused use cases.

Scale/Size Images

Select a product:

backpack

camera

flammschale

garlicpress

magnesium

microphone

rittersport

Scale and Size Images, i.e., size comparison images, have the task of making the dimensions of a product understandable by showing it in relation to a known object. This helps customers to realistically estimate the size and avoid wrong purchases.

This scenario proved to be the most demanding task in the entire test, achieving the worst overall ratings. The models showed fundamental difficulties in depicting correct proportions, size ratios, and a credible perspective, which was reflected in the lowest realism score of all categories.

In the updated comparison, GPT Image 2 leads this category and is clearly stronger than earlier OpenAI models. It follows prompts more precisely and produces more logical layouts.

The other models fail at this task. The Flux models and GPT Image 1 in particular have visible difficulties in correctly representing scale, which is expressed in incorrect and unnatural proportions. Interestingly, most models understood the instruction in the prompt but could not correctly apply the physical laws of proportion and perspective.

Conclusion: Correct size-ratio representation remains one of the biggest weaknesses of AI image models. GPT Image 2 delivers the strongest results in the updated test, but proportions, scale references, and perspective still require careful review.

Seasonal Gift Images

Select a product:

backpack

camera

flammschale

garlicpress

magnesium

microphone

rittersport

Seasonal images position a product as an ideal gift for a specific occasion like Christmas, Easter, or Valentine’s Day. They create an emotional, thematically appropriate atmosphere to increase the incentive to buy.

This scenario was among the better-rated in the test. The models reliably followed the instructions for seasonal themes, but the results were often unconvincing in their final aesthetics and visual impact.

In this category, GPT Image 2 is also among the strongest models in the updated comparison. Images often look more polished and visually coherent than with GPT Image 1.5, while prompt execution remains precise.

Although GPT-Image-1.5 precisely followed the specific requirements for seasonal gift images, the resulting product images often lacked realism.

In the mid-range, Flux.2 Pro showed a balanced performance, delivering images with a good overall impression and realism, even if the prompts were not always followed precisely. The biggest deficit was with GPT Image 1, whose images were the least aesthetically appealing. Even when the instructions were followed correctly, the overall visual impression was the weakest here.

Conclusion: Stronger models generally handle seasonal image intent well. In the updated comparison, GPT Image 2 leads through a strong combination of prompt execution and composition quality, while product depiction still needs manual verification.

Evaluation

After extending the test with GPT Image 2, there is a new overall winner: GPT Image 2. With an overall score of 3.7, it takes first place in the updated comparison and moves ahead of Gemini 3 Pro.

The Overall Result

In the updated test, GPT Image 2 reaches 3.7 for overall impression, 3.4 for realism, and 4.2 for prompt accuracy, resulting in a total score of 3.7. These values place it ahead of Gemini 3 Pro in the overall ranking. Gemini 3 Pro remains one of the strongest and most consistent models in the original benchmark.

GPT Image 2’s lead is driven mainly by the combination of high prompt accuracy, improved realism, and much stronger text rendering. This is especially relevant for Amazon-focused outputs such as infographics, application images, and explanatory product visuals.

The overall impression – a combination of image composition and visual impact – confirms this picture:

It is still important to note that even the new overall winner is not automatically the best choice for every niche. In rendering, Gemini 2.5 Flash Image remains a strong option for specific product types and visual goals.

The Technical Discrepancy: Understanding vs. Photorealism

A detailed analysis of “Prompt Accuracy” and “Realism” still shows a systematic pattern across models: AIs interpret instructions correctly in terms of content but continue to hit limits in photorealistic implementation.

Prompt accuracy is very high for GPT Image 2 at 4.2. This means requested elements are usually placed correctly and in a more coherent structure.

Realism remains the technical bottleneck. GPT Image 2 reaches 3.4, which is clearly below its prompt-accuracy score, but still a notable improvement over GPT Image 1.5 and GPT Image 1.

GPT Image 2 narrows the gap between understanding and realism, but it does not close it completely. Product details, material structures, and scale fidelity still need close quality control.

This observation is supported by statistical analysis: a strong correlation between realism and overall impression confirms that photorealistic rendering is the decisive factor for image quality, while prompt accuracy correlates much more weakly with the other criteria.

Model-Specific Observations

Beyond the quantitative ratings, certain model-specific characteristics emerged during testing:

• Flux (Pro & Flex): The results were ambivalent. Although the models often produced aesthetically pleasing images, they lacked consistency. The Flux.2 Pro model recorded the test’s lowest individual score (1.0) in the Lifestyle / Garlicpress scenario and showed a notable weakness in the “Scale/Size” scenario. Another technical detail: Flux often generated images in the format of the input image instead of the size defined in the prompt, though this can be manually adjusted in the task settings.

• GPT Image 1: This model is notable for a consistent soft-focus effect. Although the prompts are implemented solidly, the artificial “soft look” appears unrealistic and severely limits its usability for e-commerce. With an overall score of 2.0, it performed the worst in the test.

• GPT Image 1.5: As with its predecessor, this model typically applies a very strong bokeh effect, leaving the background with hardly any recognizable details. In an ecommerce context, this stylistic choice is often used deliberately to keep the product clearly in focus. Notably, the GPT models apply this effect much more aggressively than Gemini or Flux.

• GPT Image 2: Compared to GPT Image 1.5, this model shows clear progress. Most notably, text rendering is nearly error-free in the tested examples, label/icon placement is more logically tied to real product areas, and product depiction is more realistic overall. At the same time, GPT Image 2 is not a fully automated replacement for human review: product details, macro outputs, size ratios, and occasional hallucinations still require manual checks.

Conclusion

With GPT Image 2, the result of this benchmark shifts meaningfully. Gemini 3 Pro was the most reliable choice in the original comparison, but the new OpenAI model now takes the top position in the updated test. The progress is especially visible in Amazon-relevant image types such as infographics, application visuals, and explanatory product graphics: text is more reliable, labels and icons are mapped more logically to product areas, and overall compositions look more professional.

Input is crucial for image quality: detailed context, such as reference images or precise bullet points, is key to achieving precise results. For example, when we only provided a product’s main image, the models often struggled to correctly represent details from other perspectives.

Overall, the results show that AI models deliver strong practical value in e-commerce, but they are still not fully automatic solutions. Product consistency, macro details, size ratios, and photorealistic fidelity still require manual validation. The best outcomes come from precise prompts, reliable product data, suitable reference imagery, and human curation. It also remains useful to test multiple models, because product type, image category, and visual style can change which model performs best.

FAQ

Which AI is best for product images?

In the updated test, GPT Image 2 achieved the best total score and is currently the strongest option for the tested Amazon product-image scenarios. It was especially convincing in text rendering, prompt accuracy, infographic structure, and overall composition. Gemini 3 Pro remains a very strong model and can still be a suitable alternative depending on the use case.

What are the biggest challenges for AI image models?

Current models still show their greatest weaknesses in photorealistic product details (for example in macro shots), accurate size-ratio representation, and consistent product depiction across perspectives. GPT Image 2 improves these areas, but does not fully solve them.

Why does GPT Image 2 lead in the updated test?

GPT Image 2 reached the highest total score in the updated comparison. Key drivers were very high prompt accuracy, much stronger text rendering, and a more coherent semantic structure in infographic outputs. At the same time, model selection remains use-case dependent: Gemini 3 Pro and other models can still be the better choice for specific product types and visual goals.

What is important for good AI product images?

The quality of the input is the decisive factor. Detailed prompts with precise instructions (e.g., bullet points) and reference images are key to high-quality results. The more context the AI has, the better it can generate the desired images.