Etched closed a $300 million Series C at a $10.3 billion valuation, doubling from $5 billion in December when it raised $500 million, co-founder and COO Robert Wachen told TechCrunch.

Sequoia led the round, with Andreessen Horowitz, SK Hynix, Jane Street, and Diffusion Capital participating. Earlier backers include Peter Thiel, Andrej Karpathy, Dylan Field, and Amjad Masad.

The company says this marks the highest valuation ever for a Sequoia-led Series C. Founded by three Harvard dropouts in 2022, Etched has already booked $1 billion in orders for its AI inference systems.

Custom silicon for any AI model

Etched builds specialized chips and memory components that accelerate AI inference without requiring GPUs. The systems can run any AI model, including Mixture of Experts architectures like DeepSeek and Qwen, as well as non-transformer designs like Mamba.

The company designed two new components from scratch to speed up inference — the computing process after a user submits a prompt. "Inference is built in two stages," Wachen explained, "prefill and decode."

The prefill phase involves understanding the prompt and context, requiring intensive computation. The decode phase generates the actual response tokens.

Etched launched when building chips specifically for transformer-based AI models was considered risky. The company has battled perceptions that its products only run specific large language models.

Last month, Etched announced it had successfully manufactured its homegrown chips and that first full systems were being tested by clients. The company sells complete systems rather than standalone chips.

Google is reportedly pursuing similar concepts with its Frozen v2 chip for Gemini, etching parts of AI model architecture directly into silicon for performance gains.

Etched plans to use the funding to scale manufacturing and expand its engineering team as demand for AI inference infrastructure grows across enterprise customers.