Vitalik Buterin Tests AI Setup with Enhanced Privacy Features

Ethereum co-founder Vitalik Buterin has tested a privacy-focused AI setup that uses a local model, zkAPI, and Tor to generate personalized diet and exercise recommendations while limiting personal information sent to remote models.

The setup, which Buterin described as a three-layer privacy setup, covers the content of requests, payment information, and internet traffic.

Buterin used Alibaba's Qwen 3.8-Flash-Next as the local model, which handles the first layer by constructing queries itself instead of sending his original wording and full personal context to remote AI systems.

The second layer uses zkAPI to separate payments from individual AI requests. zkAPI was introduced by the Ethereum Foundation on October 1 and allows users to pay for metered APIs without linking individual requests to their identity.

Buterin said the local system decides what information a remote model needs and rewrites requests before sending them, reducing the chance that personal details or his writing style reveal his identity.

The third layer provides by Tor, which hides the user's normal IP address from the services receiving network requests.

Buterin noted that Tor was not designed for the type of request-by-request unlinking he wants, and that Tor produced latency roughly 10 to 100 times higher than what he considered desirable in his testing.