// TECHCRUNCH — INTELLIGENZA ARTIFICIALE
Silicon Valley’s AI wunderkind launches Underdog, the most private Instinct/Muse competitor yet
When self-taught coder Sigil Wen was 17, he moved to Silicon Valley and lived in an AI hacker house with famed AI researcher Andrej Karpathy.
While there, he hacked and coded alongside other people who would become the biggest names in AI, like Perplexity founder Aravind Srinivas and OpenAI researcher Noam Brown. He tested early versions of AI tools that would later become well known, including a chatbot shared by Anthropic co-founder Ben Mann that would become Claude, an image generator from David Holz that would become Midjourney, and what would become OpenAI’s GPT-3 and the image generator Stable Diffusion. Prominent investor and entrepreneur Naval Ravikant hired him for Airchat, Ravikant’s now-defunct rival to the Clubhouse social network.
For fun, he figured out how to get GPT-2 running on his Apple Watch. “It was a magical time,” Wen told TechCrunch.
Now a Thiel Fellow — the program from investor Peter Thiel that invites young founders to pursue projects instead of college — Wen on Monday launched an invite-only beta of Underdog, one of the most private AI assistants Silicon Valley has yet to offer. The model runs wholly on-device, meaning the user’s data remains on devices they already own, currently Macs and Windows PCs, with Linux, iPhone, and Android versions coming soon.
Wen built Husky, an inference engine, or software that runs AI models, and Husky is designed to run fast. Unlike other on-device engines, Wen says, it moves less data between the computer’s main chip and its graphics chip.
Underdog has other security features baked in, too, like encrypting the keys to the email and other accounts that users authorize Underdog to access.
Underdog is, however, using much smaller models than today’s state-of-the-art ones hosted in data centers. It currently uses a 27-billion parameter reasoning model fine-tuned from Qwen3.8-27B.
Wen argues that this model compares favorably with Claude Opus 4.6 in some benchmarks, or what was considered top performance six months ago. He says that means it can handle the everyday tasks that people want an AI assistant to do, like shopping research or answering math homework questions.
“You don’t need to sacrifice your privacy for the capability because they’re just as capable,” Wen says. He adds that small on-device models will continue to grow more capable over time.
Perhaps the most interesting thing about Underdog is its early business model. The app will be free at first and never ad-supported. Since the AI runs on users’ machines, Underdog doesn’t have the giant overhead of paying a provider for inference. “I don’t have to charge you a subscription to run this because my costs are so super low,” he said.