Generative AI vs. reality: how do virtual try-ons compare to real on-model content?

Generative AI has arrived with a bold promise: to reinvent the way fashion visuals are created by making the process faster, cheaper, and easier. For an industry where real model photoshoots can be expensive and slow, this sounds almost too good to be true. But can AI actually match the quality and authenticity of a real photoshoot?

We ran a full professional shoot with a model and a mannequin, and pitted it against a virtual one powered by today’s most talked-about AI tools with AI fashion models. Four background generators, three video generators, and one true-to-reality product photo of a dress on a mannequin stood at the center of the experiment. The challenge? See how close AI can get to the real thing.

Will Nano Banana Pro outshine the competition in AI fashion photography? How much do these tools distort or elevate the look of products and AI-generated models? And, ultimately, can fashion brands trust AI to replace traditional production?

The answers might surprise you. Let’s dive in.

AI technology in the fashion industry

The technology changed the pace of fashion marketing, and it has never been more embedded in the creative process. Brands are now relying on AI not just to assist but to generate imagery for both campaign assets and product pages (PDPs). This shift is altering how fashion visuals are conceived, produced, and monetised.

Generative image models and specialised AI workflows are increasingly tailored for fashion use cases. On-model photos, brand-specific assets, and even automated ad generation are now possible in minutes.

On the “model” side of things, as pointed out in The Interline’s article, some AIs generate realistically-looking virtual models and lifestyle backgrounds, allowing brands to visualise garments on diverse bodies, backgrounds, and scenarios without booking a physical studio. Industry example? You got it. The extremely visible move by H&M to work with models and agencies to create “digital twins” is setting a new benchmark in rights, representation, and reuse of model likenesses. In their initiative, models retain ownership of their digital replicas, are compensated, and may even license their twin to other brands.

We know brands are already experimenting with generative AI to create content for all kinds of purposes. But the product detail page (PDP) content is different. Here, the visuals must be trustworthy, accurate, and high-quality. Otherwise, there’s a real risk of overpromising or underdelivering. Customers may receive something that looks far from what they expected, which damages brand credibility and can drive up return rates (and we already know how big a problem it is in e-commerce). In other words, a tool meant to save money in one part of the workflow can easily end up hurting businesses.

That’s why we decided to check the capabilities of AI in terms of the fashion industry and compare it with a real photoshoot session.

💡Want to see how AI responds to the challenge of doing perfume lifestyle shots? Check out our previous blog post: State of generative AI technology for product photography: creating lifestyle perfume shots with AI.

The test base

Now, in our previous article about AI technology in lifestyle perfume photography, we compared 5 different AI models/tools and tried to achieve professional results with a simple prompt. This time, however, the prompt is more advanced; we used two Orbitvu solutions to produce content, and there are two types of photos: on-model (created in Fashion Studio as reference images/videos) and packshots (created in Alphastudio XXL as source images for generative AI).

The goal is to achieve the same quality and authenticity as the original photos done in Fashion Studio, but in the AI process.

Packshots & model shots

AI tools: image and video

We will test 4 popular AI image-to-image generators to create two on-model pictures from two source ghost images (front and back). Then, using the best two on-model images and 3 state-of-the-art image-to-video generators on the market, we will try to replicate the original video.

Image-to-image AI models:

Google Nano Banana PRO - Nano Banana is the next-generation AI image generator/editing platform (powered by Google’s Gemini 3.0 model) that lets you turn text into images, edit photos with simple language, maintain visual identity across edits, and fuse multiple images, all designed for creators needing high-quality and consistent visuals. The latest update enables users to generate images at higher resolutions, including 2K and 4K, in addition to the standard 1 K resolution.
Flux Kontext [PRO] - FLUX 1 Kontext is a next-generation AI image model by Black Forest Labs that combines text prompts and image inputs to create or edit visuals with strong context‐awareness, object/character consistency, and professional-grade output.
Seedream 4.0 by ByteDance - Seedream is the next-generation multimodal AI image model. It blends generation and editing, works with both text and images, supports multiple reference inputs, and delivers ultra-high-resolution visuals quickly. Its multimodal “reasoning” capabilities make it more than just an art toy. It's positioned for professional workflows.
ChatGPT - the ChatGPT AI Image Generator is a feature built into OpenAI’s ChatGPT that allows users to create and edit images using natural language. Powered by DALL-E 3, it enables you to generate detailed visuals directly from text prompts or modify existing images with simple instructions. ChatGPT is also very useful for creating prompts and task ideas.

Image-to-video AI generators:

Veo3 - a next-generation text-to-video and image-to-video tool from Google. It allows users to input a text prompt (or optionally reference images) and automatically generate short cinematic clips with synchronized audio, realistic motion, and high visual fidelity.
Kling AI - an AI video-generation platform developed by Kuaishou Technology in China. It supports converting text prompts (and even static images) into dynamic videos with realistic motion and cinematic style.
Seedance 1.0 PRO - an advanced AI video generation model developed by ByteDance (the creators of TikTok). It specializes in converting text prompts and static images into high-quality, cinematic videos (up to 1080p).

Testing AI tools: which AI image generator is best at generating fashion PDP images?

With today's advances in AI technology, is it possible to create content that doesn’t deviate too much from reality? Are the imperfections that we saw a moment ago in every image generated by artificial intelligence still visible? Let’s take a closer look at the popular AI tools on the market and check whether a good packshot and a good prompt will be able to replace a full photo shoot for e-commerce.

The criteria we will evaluate are primarily whether artificial intelligence will generate images for us:

Consistency: how the two images of the same garment, both front and back, are consistent in terms of model look, accessories, and overall garment consistency.
Product fidelity: whether the product we photographed, in this case, a dress, is represented faithfully, including colors, patterns, its shape, and size. How realistically does it fit on the model?
Costs: is it worth the money?
Prompt adherence: are all the instructions followed?