TryDrobe vs Fashn.ai

Fashn.ai is an API-first virtual try-on platform built for developers and e-commerce engineering teams. Rather than offering a consumer-facing application, Fashn provides a REST API with official TypeScript and Python SDKs that let developers integrate virtual try-on directly into their own products and workflows. Their latest model, V1.6, has been pre-trained on over 18 million try-on examples, giving it strong performance across a wide range of garment types and body poses.

Pricing follows a pay-per-generation model at $0.075 per image, with no subscription required. This makes it accessible for teams that want to experiment or run variable volumes without committing to a monthly plan. Results are generated in 5 to 17 seconds depending on the selected model and input complexity. New accounts receive 10 free credits to test the platform.

Beyond basic try-on, Fashn offers several additional endpoints including Product-to-Model (placing garments on AI-generated models), Face-to-Model (generating a model from a face photo), Model Create, and Background Remove. The platform supports multiple input types including flat-lay product photos, ghost mannequin images, and standard on-model photography, making it versatile for e-commerce product pipelines.

TryDrobe is a consumer-facing virtual try-on platform that lets anyone upload a photo and see how clothing looks on them instantly. The platform includes a digital closet for saving and organizing items you own or are considering, plus an outfit planner for putting together complete looks. It is available as both a web application and a native iOS app.

For individual consumers, TryDrobe offers subscription plans starting at $4.99 per week, providing a set number of try-on credits each billing period. The platform is designed for everyday shoppers, fashion enthusiasts, and stylists who want to visualize outfits without writing any code or dealing with APIs.

TryDrobe also offers a Shopify plugin for merchants, with business plans ranging from a free tier (10 guest credits per month) up to $99 per month for high-volume stores. The plugin installs directly from the Shopify App Store and adds a try-on button to product pages. Merchants get access to an analytics dashboard to track try-on usage and customer engagement.

Fashn.ai is squarely aimed at developers and e-commerce engineering teams who want to build custom virtual try-on experiences. If your team has the technical resources to integrate an API, build a custom UI, and handle image processing pipelines, Fashn gives you the building blocks to create exactly the experience you want. Their SDKs and documentation are designed for technical users who are comfortable working with REST APIs.

TryDrobe targets a completely different audience: individual consumers who want to try on clothes before buying, stylists working with clients on outfit selections, and Shopify merchants who want to add try-on functionality to their stores without hiring developers. The platform is designed to be used immediately with no technical setup required.

There is very little overlap between these two audiences. A developer building a custom try-on feature for a large e-commerce platform would naturally gravitate toward Fashn, while a boutique owner on Shopify or a consumer shopping online would choose TryDrobe. The products solve the same underlying problem — virtual try-on — but for fundamentally different users.

Getting started with Fashn.ai requires development work. You need to sign up for API keys, integrate the REST API into your application, build a user interface for uploading photos and displaying results, and handle image storage and processing. The TypeScript and Python SDKs simplify the API calls, but you still need a developer to build and maintain the integration. For teams with existing development resources, this is a straightforward process.

TryDrobe takes the opposite approach. The Shopify plugin installs from the Shopify App Store in minutes and requires no coding whatsoever. You configure a few settings, and a try-on button appears on your product pages. For the consumer app, there is nothing to integrate — users simply sign up, upload a photo, and start trying on clothes immediately.

For non-technical store owners and individual users, TryDrobe is the clear choice. For engineering teams building a bespoke experience within a larger platform, Fashn provides the flexibility and control that an API affords. The right choice depends entirely on whether you have developers available and whether you need a custom implementation.

Fashn.ai uses a pay-per-image model at $0.075 per generation with no monthly subscription. This works well for teams with low or unpredictable volume, since you only pay for what you use. There are no tiers, no feature gates, and no monthly commitments. Ten free credits are provided to new accounts for testing.

TryDrobe uses a subscription model. Consumer plans start at $4.99 per week, while business plans for Shopify merchants range from free (10 credits/month) to $99 per month (1,000 credits with analytics and priority support). The subscription provides predictable monthly costs and bundled features like the digital closet, outfit planner, and merchant analytics.

To put the pricing in perspective: a Shopify store doing 500 try-ons per month would pay approximately $37.50 with Fashn (plus development costs for the custom integration). With TryDrobe Business Pro at $49 per month, you get 400 credits plus the analytics dashboard, Shopify plugin, and product discoverability in the TryDrobe consumer app — with no development costs. The total cost of ownership depends heavily on whether you factor in engineering time.

Fashn.ai outputs try-on images at 576x864 resolution and supports a diverse range of input types including flat-lay product photos, ghost mannequin images, and standard on-model photography. Their model has been trained on 18 million try-on examples, and they offer technical controls like garment category selection and mask adjustment to fine-tune results. The platform is designed to give developers maximum control over the generation process.

TryDrobe uses Google's Gemini API as part of its try-on pipeline, optimizing for consumer simplicity rather than technical configurability. The platform handles all image processing behind the scenes — users simply upload a photo and a clothing image, and the result is returned automatically. There are no technical parameters to adjust, which is by design for a consumer audience.

Both platforms preserve garment details like prints, textures, patterns, and colors in their try-on results. Fashn offers more granular control for developers who want to tune the output, while TryDrobe prioritizes a frictionless experience where the technology stays invisible to the end user. The quality difference is less about which is better and more about which workflow matches your needs.