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Opera introduces a new web standard to let users deploy AI locally in their browser

Opera introduces a new web standard to let users deploy AI locally in their browser

techcrunch.com 27.10.2026 14:00 5 views
The new standard, WebAI, is designed to work with a variety of AI models.

Browser maker Opera has introduced a new web standard that lets users to run AI models directly in its browser, without relying on the cloud. The new standard, WebAI, is designed to work with a variety of AI models. Opera name drops Google’s Gemma — an open-weight model that Google first introduced two years ago — as one example.

On Macs, WebAI also supports Apple’s on-device foundation model, the company says. But Opera says WebAI isn’t tied to any particular model and is built to support a wide range of open-weight AI systems. WebAI grew out of previous work by Opera to bring locally run models into its browsers.

Opera is making the new AI features available as an early preview in its flagship Opera One browser. The company says Opera GX, its browser built for gamers and streamers, and Opera Neon, its browser that uses AI agents to perform tasks, will soon get the same treatment. Users have to choose to opt into the feature, according to the company.

Open-weight models offer a number of benefits to users. For one, they are typically free to download and use. Their underlying model weights are also publicly available, which gives developers more freedom to customize how they work.

Although unlike fully open-source software, open-weight models still come with some restrictions. There’s the additional advantage of privacy, the company said. Users can tap into AI features without having to send their personal information to a company’s servers or pay for a cloud-based AI subscription.

Privacy has become a growing concern as AI assistants become more powerful and gain access to personal information. Users often surrender vast amounts of personal information with AI chatbots, sometimes without a clear understanding of how that data is stored or used. Locally run models offer an alternative because the processing happens on the user’s own device — and not on a company’s cloud server.

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