Etched, an AI chip startup launched in 2022 by three Harvard dropouts, has secured a $300 million Series C funding round at a $10 billion valuation. The round was led by Sequoia, with participation from Andreessen Horowitz, SK Hynix, Jane Street, and Diffusion Capital, along with earlier investors. Other notable backers include Peter Thiel, Andrej Karpathy, Dylan Field, and Amjad Masad. The company was previously valued at $5 billion in December when it raised a $500 million round, meaning its valuation has doubled in about seven months. Etched claims this is the highest valuation ever for a Sequoia-led Series C. Last month, the company announced it had successfully manufactured its homegrown chips, that its first full systems were being tested by clients, and that it had already booked $1 billion in orders.

Etched launched at a time when building a chip specifically for AI models based on transformer technology—the architecture behind most modern AI systems like ChatGPT and Claude—was considered unconventional, if not eccentric. The company is still working to overcome the perception that its products, sold as complete systems rather than just chips, are designed to run only specific large language models. Wachen explains that this is not the case. The systems can run any AI model, including Mixture of Experts models like DeepSeek and Qwen—which split tasks across specialized sub-models instead of relying on one large model—as well as non-transformer designs like Mamba, which is built on a different underlying architecture known as a state-space model. Interestingly, the idea of etching parts of a specific AI model directly into silicon to enhance performance is no longer seen as far-fetched. Google is reportedly pursuing a similar concept with its Frozen v2 chip for Gemini.

Despite this, Etched’s current claim to fame is that it designed two new components from scratch to accelerate inference—the computing process that occurs after a user submits a prompt. “Inference is built in two stages,” Wachen says, “prefill and decode.” The prefill phase involves understanding the prompt, including context, and is mathematically and computationally intensive. The decode phase generates the output tokens, or the actual answer the user sees, which requires less computation but massive amounts of memory. Etched created a prefill chip that operates “dramatically” faster, he promises, “by running at a much lower voltage than any other AI chip. We call this low-voltage inference.” Lower voltage generates less heat, allowing the chip to pack in more transistors. For the decode process, Etched developed a new type of memory and “interconnect technology that we call cluster scale memory. It allows many chips to connect together and use a shared memory pool at a very, very fast, low latency,” he says. The result, Etched promises, is high speeds with lower costs.

Because the startup launched before most of the tech world—aside from Nvidia—understood AI’s specialized compute needs, founders CEO Gavin Uberti, Wachen, and CTO Chris Zhu have faced plenty of skeptics who continued doubting even after the company announced that its first batch of silicon had been successfully manufactured by TSMC. Much of that skepticism stems from how few people have had access to the systems. So far, access has been limited to investors and early customers. In fact, that’s how Etched landed its list of famous investors—by showing them private demos in its office. “Andrej Karpathy from Anthropic, Noam Brown from OpenAI, Geoffrey Hinton, as well as all the investors in the funding round—these are all people who actually tried the hardware and are very excited about it,” Wachen says. Still, it’s been a long, difficult road, with more challenges ahead before the rack systems are mass-produced and delivered. The trio famously dropped out of Harvard to launch Etched, not knowing then how to raise cash—much less the large amounts they would need—or how to hire. “We had no idea how hard it was going to be,” he said. “I think we still have to be humbled by what it will take to actually get to scale.”

Wachen recalls arriving in the Bay Area after telling his parents he was leaving school to start a company, with no office or apartment arranged. He slept on the floor of a friend’s unfurnished house. “I remember staying in my friend’s house that they were about to sell, using a towel as a blanket,” he laughs. The founders eventually set up the servers they needed to run the chip-design tools in the garage of an early employee, and “every time it needed to be rebooted, he would call his wife, and she would go and hit the reboot button.”

Today, there are 400 people bustling in an office, and Etched operates a 2-megawatt data center. “We’re running tokens in our lab today, working with some of the largest AI companies in the world,” he says. Wachen also has a blanket now, along with a mattress “and a pillow even. Multiple pillows,” he jokes. More importantly, he and his co-founders never let the doubters stop them. “It’s come a long way. It’s a very, very different world. But I think, when you really think something’s possible, and you just work at it for a long time, you can do it.”