CatalogX Now Powered by Gemini AI: Faster, More Affordable Try-On

Today we're announcing a major upgrade under the hood at CatalogX: our default AI engine for virtual try-on and fashion mockup generation is now Google's Gemini AI, replacing OpenAI's GPT-Image-2 as the default provider. The result is faster generation, native high-resolution output, and lower per-generation costs that we're passing directly to you.

If you're an existing CatalogX user, here's the important part: your workflow doesn't change at all. The interface, upload flow, and output format are identical. The only difference is what happens behind the scenes — and it's all better.

What Changed?

Previously, CatalogX used OpenAI's GPT-Image-2 as the default AI engine for all virtual try-on and mockup generation. Every time you uploaded a garment image and selected a model, pose, and background, GPT-Image-2 handled the generation.

Starting today, Gemini (via our Nano Banana provider) is the default engine for all new users. If you're an existing user, your current engine setting remains unchanged — you'll continue using whatever engine you were on. You can switch to Gemini from your account settings at any time.

GPT-Image-2 isn't going away. It remains fully available as an alternative engine for users who prefer it. This isn't a replacement — it's a new default, with the previous option still accessible.

Why Gemini?

We evaluated multiple AI providers over the past several months. Gemini stood out for three reasons that directly benefit fashion sellers:

• Native high-resolution output (2K/4K): Gemini generates images natively at 2K and 4K resolution. With GPT-Image, high-resolution output meant generating at 1024px and then upscaling. Gemini skips the upscaling step entirely — the detail is genuine, not interpolated.
• Faster generation times: Gemini consistently produces results faster than GPT-Image-2 in our benchmarks. For sellers generating dozens or hundreds of mockups per day, this adds up to meaningful time savings across a catalog.
• Lower per-generation cost: Gemini's API pricing is more economical, and we're passing those savings directly to users. The same plan, the same price — but each credit goes further. You get more generations per rupee spent.

What Stays the Same

Everything you interact with in CatalogX is identical. The engine change is entirely behind the scenes. Specifically:

• Same upload flow: Upload your garment image exactly as before — drag and drop, click to browse, or use the API.
• Same garment types: All supported garment categories (sarees, kurtis, lehengas, shirts, dresses, etc.) work with Gemini.
• Same pose controls: All model poses and body types are available. The pose library hasn't changed.
• Same model library: Every AI model in the CatalogX library works with Gemini. No models have been removed or changed.
• Same background options: All backgrounds — studio, lifestyle, custom — are available exactly as before.
• Same output formats: You still get PNG and JPG downloads in the same dimensions and file structure.

Quality is comparable across both engines. In our internal testing with thousands of garment images across multiple categories, Gemini matched or exceeded GPT-Image quality in the vast majority of cases. The differences, where they exist, are subtle and vary by garment type.

Native 2K and 4K: No More Upscaling

This is the most technically significant improvement. With GPT-Image-2, the maximum native generation resolution was 1024x1024 pixels. To deliver higher-resolution mockups (which fashion marketplaces require), CatalogX would generate at 1024px and then use AI upscaling to reach 2K or 4K.

Upscaling works — CatalogX's HD Upscale tool is proof of that. But upscaled images are fundamentally different from natively generated high-resolution images:

• Upscaled images start with 1024px of real detail and use algorithms to interpolate additional pixels. The extra resolution is educated guesswork — sharp edges and fabric texture are reconstructed, not originally rendered.
• Natively generated 2K/4K images contain genuine detail at every pixel. The AI model renders fabric texture, stitching, embroidery, and draping at full resolution from the start. There's no interpolation step.

The difference is most visible in fine details: embroidery patterns, fabric weave, print sharpness, and garment edges. A natively generated 4K image of a heavily embroidered lehenga will show thread-level detail that an upscaled 1024px image cannot reproduce, because that detail was never in the source generation.

GPT-Image Is Still Available

We're not removing GPT-Image-2 from CatalogX. If you've been getting great results with it and prefer to stick with what works, you can.

• Existing users: Your current engine setting is unchanged. If you were using GPT-Image, you're still on GPT-Image.
• Switching engines: You can switch between Gemini and GPT-Image from your account settings, or contact support for assistance.
• Testing both: Some garment types may produce slightly different results between engines. If quality is critical for a specific product category, we recommend generating a few test mockups with each engine to compare.

Both engines receive the same CatalogX prompt engineering and post-processing pipeline. The difference is in the underlying generation model, not in how CatalogX prepares or processes the output.

What This Means for Your Workflow

Nothing changes in how you use CatalogX. The upgrade is automatic for new accounts and optional for existing ones. Here's the practical impact:

• Faster turnaround: Generations complete faster, so you spend less time waiting and more time listing products.
• More credits per rupee: Lower per-generation cost means your existing plan goes further. Same price, more mockups.
• Better high-res output: Native 2K/4K means genuinely sharper mockups for marketplace listings that require zoom-quality images.
• Same learning curve: Zero. If you know how to use CatalogX today, you already know how to use the Gemini-powered version.

If you're a new user signing up today, Gemini is your default engine. You don't need to configure anything — just upload your garment and generate.

Frequently Asked Questions