# AI chip startup Etched more than doubles valuation to $10.3B in new $300M round > Source: > Published: 2026-07-24 01:29:06+00:00 ### AI chip startup Etched more than doubles valuation to $10.3B in new $300M round Etched Inc., a startup with a chip optimized for artificial intelligence inference, today [announced](https://www.globenewswire.com/news-release/2026/07/23/3332366/0/en/Etched-raises-300M-at-a-10-3B-Valuation-to-Scale-Production-of-Frontier-Scale-Inference-Hardware.html) that it has raised $300 million in funding. The Series C round was led by Sequoia. SK Hynix Inc., the world’s largest supplier of memory for AI chips, participated as well alongside Andreessen Horowitz, Jane Street and Diffusion. Etched is now valued at $10.3 billion, more than double what it was worth in December. Nvidia Corp.’s popular graphics cards are designed to run both AI training and inference workloads. According to Etched, optimizing its chip solely for the latter use case enabled it to develop a more efficient design. The company plans to ship the processor as part of an appliance equipped with custom cooling components and interconnects. When an AI model receives a prompt, it kicks off the inference workflow by performing so-called prefill processing. That step helps the model understand the prompt’s meaning. The task is carried out with matrix multiplications, hardware-intensive mathematical calculations that differ significantly from a regular multiplication. The number of matrix multiplications that a chip can perform per second is tied to its clock frequency. The higher the frequency, the more calculations the chip can complete. Traditional GPUs must limit their clock frequency to avoid generating excess heat. According to Etched, its chip avoids GPUs’ thermal bottleneck using a mechanism dubbed LVI. The technology minimizes the processor’s voltage, which in turn lowers its temperature. That enables it to operate at higher clock frequencies than graphics cards. The prefill phase of the inference workflow is followed by a so-called decode stage. During that step, AI models generate a response to the user’s prompt one token at a time. Etched’s chip speeds up decode calculations with a mechanism dubbed Cluster Scale Memory. It enables all the accelerators in a rack to share the same memory. When a piece of data is kept in shared memory, there’s no need to send a separate copy of the data to each accelerator. That makes the prompt processing workflow more efficient. “The infrastructure required to serve frontier AI sustainably and economically was never going to come from incremental improvements to existing hardware,” said co-founder and Chief Executive Officer Gavin Uberti (pictured, right). “This round reflects a growing industry conviction that the challenge demands a new entrant willing to rebuild the stack from first principles.” Etched plans to start shipping its first racks this summer. The company is building an SMT, or surface mount technology, production line to expedite the assembly of its appliances. The production line will be located in a 80,000 square-foot facility near the company’s San Jose headquarters that also functions as a prototyping lab. ##### Photo: Etched # A message from John Furrier, co-founder of SiliconANGLE: Support our mission to keep content open and free by engaging with theCUBE community. **Join theCUBE’s Alumni Trust Network**, where technology leaders connect, share intelligence and create opportunities. **15M+ viewers of theCUBE videos**, powering conversations across AI, cloud, cybersecurity and more** 11.4k+ theCUBE alumni**— Connect with more than 11,400 tech and business leaders shaping the future through a unique trusted-based network. # Are you AWS customer? 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