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Tamara News  /  Blog  /  ChatGPT
03 Oct 2026
ChatGPT virtual try-on feature displayed in a shopping conversation

ChatGPT Will Now Show You Wearing the Clothes Before You Buy

Categories Tech

OpenAI rolled out a ChatGPT virtual try-on feature this week. It gives users a way to see clothing on their own photo before buying it. The company announced the tool on Thursday, October 1. A second new feature, called Favorites Library, launched alongside it. Both additions build on ChatGPT’s existing shopping results. Together they mark OpenAI’s latest push to turn the chatbot into a shopping assistant, not just a search tool for products.

With the new tool, a user uploads a selfie or a full-body photo. A “Try On” button then appears next to items in ChatGPT’s shopping results. Tap it, and ChatGPT generates an image showing that person wearing the item. Users are not limited to products ChatGPT surfaces on its own. They can also upload a photo of an item instead, such as a screenshot from a retailer’s website. ChatGPT will then simulate that item on them, using the uploaded photo as the base image.

ChatGPT can go further than a single try-on, too. A user can describe a style they want. ChatGPT will then shop for matching pieces across retailers. The chatbot can also identify clothing in a photo, such as an outfit a celebrity wore. From there it helps the user find similar items to buy.

How the ChatGPT Virtual Try-On Feature Works

The try-on tool sits inside a normal ChatGPT shopping conversation. It is not a separate app. Once a user uploads a reference photo, the “Try On” button appears next to eligible products automatically. Selecting it triggers an image-generation step. ChatGPT then returns a picture of that person, or body type, wearing the selected item.

ChatGPT virtual try-on feature shown on a smartphone shopping app

This two-way flexibility sets the feature apart from a basic size chart or fit guide. A user can start from OpenAI’s own shopping results or from their own screenshot of a product. Either way, the feature depends heavily on image quality. A poor render would undercut the whole point of trying something on before buying it.

Images 2.5 Powers the New Try-On Tool

The try-on tool and Favorites Library both run on Images 2.5. OpenAI released this new image-generation model alongside the shopping update. OpenAI says the model produces more natural lighting than its predecessor. It also says Images 2.5 renders richer textures and follows editing instructions more reliably. Generation latency has also come down, OpenAI says, so a try-on image should appear faster than before. Faster, more instruction-accurate generation matters for a feature built around back-and-forth edits, such as asking ChatGPT to show an item in a different color or fit.

Image quality and speed matter more for shopping than for many other ChatGPT tasks. A try-on image that looks obviously fake is unlikely to change anyone’s purchase decision. One that takes too long to generate carries the same risk. OpenAI is betting that Images 2.5 clears that bar well enough to make virtual try-on a feature people actually use.

A Favorites Library for Saved Looks

Favorites Library gives users a place to save products they find while chatting with ChatGPT. Saved items sit alongside any try-on images generated for them. A user can return later to compare looks or revisit something they considered buying earlier. OpenAI has not said how long saved items stay available. It has also not said whether the library syncs across devices. For now, OpenAI describes it simply as a new library for saved products and try-on images, built to sit next to the try-on tool rather than as a standalone feature.

AI Shopping Features Have Had a Mixed Run So Far

The virtual try-on launch follows an earlier OpenAI feature called Instant Checkout. That tool let users complete purchases directly inside ChatGPT. Instant Checkout launched earlier in 2026. It did not gain significant traction. OpenAI has not said whether virtual try-on is meant to revive interest in in-chat shopping generally, or whether it will stand on its own regardless of how people check out.

OpenAI is not the first company to offer this kind of tool. Google introduced a comparable virtual try-on feature in its own shopping products back in 2025. The rivalry between OpenAI and Google now extends across AI shopping tools, not just general-purpose models. Both companies are pushing to make their chatbots useful for everyday purchases, not just information lookups. Neither company has said how the two try-on approaches compare directly, since each relies on its own image-generation system and its own retail partnerships.

Virtual try-on also lands at a moment when OpenAI has been reassessing its own product lineup. The company’s recent decision to cancel another in-progress product shows OpenAI narrowing its roadmap, even as it adds consumer tools like this one. AI shopping and agent-style features are also drawing closer regulatory attention. A separate regulatory probe into AI agents acting on users’ behalf is already underway. It is a reminder that tools letting a chatbot shop, recommend, and now visualize purchases on a user’s own photo sit in an area regulators are watching more closely.

What’s Next for ChatGPT Shopping

OpenAI has not published a roadmap beyond this week’s announcement. The company has not said whether virtual try-on will expand beyond clothing, to categories like furniture or accessories. It also has not said whether Favorites Library will add sharing or sorting tools later. And OpenAI has not explained how virtual try-on interacts with Instant Checkout for someone who wants to try on an item and buy it in the same conversation.

What is clear is that OpenAI keeps investing in shopping as a ChatGPT use case, even after Instant Checkout’s slow start. Whether virtual try-on performs differently will depend on how realistic the Images 2.5 renders look to ordinary users. It will also depend on whether a try-on image is convincing enough to actually influence a purchase, rather than simply being a novelty people try once.

ChatGPT Shopping: Your Questions Answered

What is the ChatGPT virtual try-on feature?

It is a tool OpenAI added to ChatGPT that generates an image of a user wearing a clothing item, based on a selfie or full-body photo the user uploads.

How do I use virtual try-on in ChatGPT?

Upload a selfie or full-body photo in ChatGPT, then look for the “Try On” button next to items in shopping results. Selecting it generates the try-on image.

Can I try on an item from a store I found myself?

Yes. Users can upload a photo of an item, such as a screenshot from a retailer’s website, and ChatGPT will simulate that item on them instead of only using its own shopping results.

What is Favorites Library?

Favorites Library is a new ChatGPT feature that lets users save products they find, storing them alongside any try-on images generated for those items.

What model powers the new ChatGPT shopping features?

Both features run on Images 2.5, an image-generation model OpenAI says produces more natural lighting, richer textures, more reliable instruction-following, and lower generation latency than its predecessor.

Is this OpenAI’s first shopping feature in ChatGPT?

No. OpenAI launched Instant Checkout, a feature letting users complete purchases inside ChatGPT, earlier in 2026, though it did not gain significant traction.

For more on the companies racing to build AI shopping tools, see our coverage of Google’s own AI push, OpenAI’s recent product decisions, and the regulatory scrutiny facing AI agents.

Sources

04 Sep 2026
Data center servers behind the AI chatbot outage

ChatGPT, Claude and Grok All Went Dark at Once — Here’s Why

Categories Tech

An AI chatbot outage knocked three of the world’s most-used AI tools offline within the same hour. It happened on September 3, 2026. OpenAI’s ChatGPT, Anthropic’s Claude and xAI’s Grok all began throwing errors around 7:43 a.m. Pacific time. Downdetector logged sharp spikes in error reports across all three services within minutes of each other.

Three competing AI labs rarely fail at once. Chatbots from different companies almost never share a single point of failure. The near-simultaneous timing pointed straight at the infrastructure underneath them, not at any one model.

How the AI Chatbot Outage Unfolded

ChatGPT’s disruption did not stop at the chat window. OpenAI confirmed that logins, file uploads, voice mode, search, Deep Research and image generation were all affected. Its Codex coding tool went down too, according to 9to5Mac. Anthropic said its newest Claude Opus 4.8 and Opus 5 models took the hardest hit. Older Claude models recovered to normal error rates faster. xAI’s Grok also went down, and the company acknowledged the problem publicly while it worked on a fix.

Secondary services built on top of these models felt it too. Developer tools including the coding agent Cursor confirmed downtime, since they depend on the same upstream AI infrastructure. The Register first reported that knock-on effect. All three chatbots returned to normal service by 12:38 p.m. Pacific time.

What Likely Caused the AI Chatbot Outage

Microsoft Azure was also experiencing its own outage at the same time. Several outlets, including Axios, said Microsoft’s cloud problems may have contributed to the AI outages. None of the three AI companies has published a full technical explanation yet. Tamara News has not independently verified a single root cause. This is what multiple outlets reported as the likely trigger, not a confirmed finding from OpenAI, Anthropic or xAI themselves.

The pattern fits a broader worry in the industry. Even rival AI companies often lean on the same handful of cloud providers, data center regions and networking backbones. When one shared layer stumbles, the outage rarely stays contained to a single brand.

This is not the first time a cloud provider’s problems have rippled outward into services that look unrelated on the surface. Streaming platforms, banking apps and airline booking systems have all gone dark in past incidents traced back to a single cloud region. AI chatbots are simply the newest category to join that list, and arguably the most visible one, since millions of people now open ChatGPT the way they once opened a search engine.

Why This AI Chatbot Outage Matters Beyond the Inconvenience

For casual users, an hour without ChatGPT is an annoyance. For businesses that wired these models into customer support, coding pipelines and internal workflows, it becomes a production incident. Companies that built single-vendor dependencies into critical systems had no working fallback during the window. The model they might have switched to was also down.

This is the second major cloud-linked disruption Tamara News has covered in three days. A separate Microsoft cloud outage hit a different set of services on September 2. Together, the two incidents raise the same question from different angles: how much of daily digital life now depends on a small number of cloud platforms staying up.

Enterprise customers with strict uptime requirements are the ones most exposed here. A five-hour gap in service can cascade into missed customer replies, stalled code deploys and delayed research work. Few companies have built real fallback plans for a scenario where every major AI vendor drops at once.

Some engineering teams responded by switching to open-weight models they can run on their own hardware, at least temporarily. Others simply waited it out. Either response points to the same underlying gap: most organizations that rely on AI chatbots day to day have not stress-tested what happens when none of them are reachable.

What Happens in the Days Ahead

Expect each company to publish, or decline to publish, a post-incident report in the coming days. OpenAI, Anthropic and xAI have varying track records on transparency after outages. Some post detailed timelines. Others post a short status update and move on. Enterprise customers with service-level agreements will likely ask pointed questions about compensation and redundancy planning. None of the three companies has said whether Wednesday’s incident will change how they architect around single points of failure.

AI chatbot outage error screen on a smartphone

Frequently Asked Questions

What caused the AI chatbot outage on September 3, 2026?
No company has issued a confirmed root-cause statement. Multiple outlets, including Axios, reported that a concurrent Microsoft Azure disruption may have contributed. OpenAI, Anthropic and xAI have not confirmed this independently.

How long did ChatGPT, Claude and Grok stay down?
Reports place the start of the disruption around 7:43 a.m. Pacific time. All three services returned to normal by roughly 12:38 p.m. Pacific — just under five hours.

Were all ChatGPT features affected?
Yes. OpenAI confirmed that logins, uploads, voice mode, search, Deep Research, image generation and its Codex coding tool were all disrupted, not just the main chat interface.

Did the outage affect tools built on top of these chatbots?
Yes. Developer tools including the coding agent Cursor reported downtime because they depend on the same upstream AI infrastructure.

Is this connected to the Microsoft cloud outage from September 2?
The two incidents happened a day apart and both involve cloud infrastructure. Tamara News has not seen a confirmed technical link between them.

Featured image: “BalticServers data center.jpg” by BalticServers.com (CC BY-SA 3.0), via Wikimedia Commons. In-content image: “Smartphone with ChatGPT app (52917381673).jpg” by Jernej Furman from Slovenia (CC BY 2.0), via Wikimedia Commons.

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