OpenAI Adds AI Virtual Try-On and Favorites Library to ChatGPT for Online Shoppers

OpenAI introduces a virtual try-on tool and Favorites library in ChatGPT, letting users test clothes with personal photos and save products.

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OpenAI Adds AI Virtual Try-On and Favorites Library to ChatGPT for Online Shoppers

OpenAI rolled out a virtual try-on tool and a Favorites library within ChatGPT on Oct. 1, 2026, marking a direct push into e-commerce. The San Francisco-based artificial intelligence company now lets shoppers see how apparel and fashion accessories look on their own bodies before buying. The update operates on web browsers and mobile apps across Android and iOS, taking on commercial search tools from Google and Amazon.

Key Takeaways

  • ChatGPT now includes a dedicated “Try On” button next to clothing and accessory listings.
  • Users upload a selfie or full-body picture to view generated previews of outfits.
  • The system runs on the ChatGPT Images 2.5 model for improved texture, lighting, and rendering speeds.
  • A new Favorites library lets shoppers bookmark products and organize them into folders.
  • OpenAI clarifies that generated pictures serve only as visual previews and do not guarantee actual cloth fitting or sizing.

OpenAI Adds AI Virtual Try-On and Favorites Library to ChatGPT

How the Virtual Try-On Operates

When users search for clothing items, a “Try On” button appears beside supported product listings in the chat interface. Selecting this option prompts the user to upload a clear selfie or full-body portrait. The artificial intelligence model then drapes the chosen apparel onto the user’s likeness, creating a realistic image preview.

The system relies on OpenAI’s ChatGPT Images 2.5 architecture. This image model improves fabric textures, adjusts ambient lighting to match the original photograph, and cuts generation wait times. Beyond catalogue listings, users can also upload images of garments found on external websites and ask the bot to preview them.

Saving Products in the Favorites Library

Alongside the preview tool, OpenAI added a dedicated Favorites section. Shoppers can save discovered garments, electronics, and home items directly to their ChatGPT Library. The tool allows users to sort saved items into custom folders, making it easier to compare prices and styles across multiple shopping chats without losing previous product links.

Privacy Policies and Sizing Limitations

OpenAI stated that reference photos remain saved in the user profile for future outfit checks. However, account holders retain control over their pictures. Users can delete or replace stored reference images by visiting Settings, opening Personalization, and selecting Reference Photos. By default, free personal tier accounts may have image inputs used for model training unless users manually opt out in data controls.

The company also posted a clear disclaimer regarding product fit. The visualizer generates an aesthetic representation of the style, not an exact measurement check. Shoppers must still verify traditional size charts, fabric stretch, and retailer return rules before making external purchases.

Frequently Asked Questions

Q1. How do I use the virtual try-on feature in ChatGPT?

A1. Search for clothing or accessories in ChatGPT, tap the “Try On” button on a product card, and upload a full-body photograph or selfie when prompted.

Q2. Does ChatGPT charge fees or take payments for purchases?

A2. No, ChatGPT does not process in-app checkouts. It provides direct outbound links to retail stores where shoppers complete orders.

Q3. Can the virtual try-on tell if a shirt or dress will fit my exact body size?

A3. No. The tool creates visual style previews and cannot confirm exact measurements or physical garment fit.

Q4. How do I delete my uploaded photos from ChatGPT?

A4. Open Settings, navigate to Personalization, click Reference Photos, and choose the delete option for your saved pictures.

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An MA in Mass Communication from Delhi University and 7 years in tech journalism, Shweta focuses on AI and IoT. Her work, particularly on women's roles in tech, has garnered attention in both national and international tech forums. Her insightful articles, featured in leading tech publications, blend complex tech trends with engaging narratives.
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