
By burning the transformer architecture into our chips, we’re creating the world’s most powerful servers for transformer inference.

By burning the transformer architecture into our chips, we’re creating the world’s most powerful servers for transformer inference.
Product: Sohu — transformer-optimized inference ASIC and server stack
Headquarters: Cupertino, California, United States
Founding timeframe: Circa 2022
Total reported funding: Approximately $625.4M (reported aggregate varies by source)
Notable investors: Includes Stripes, Peter Thiel, Primary Venture Partners, Two Sigma Ventures (reported participation)
Transformer-model inference performance and efficiency in AI hardware
2022
Computer Hardware Manufacturing
$5.4M
Reported seed round ~ $5.4M
$120M
Reported round bringing total raised to roughly $125M in some coverage; included participation from institutional and angel investors
$500M
Reported round valuing company at about $5B and bringing aggregate funding toward ~$1B in some reports
“Includes participation from Stripes, Peter Thiel, Primary Venture Partners, Two Sigma Ventures and other institutional and angel investors (reported)”
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About Etched Etched is building AI chips that are hard-coded for individual model architectures. Our first product (Sohu) only supports transformers, but has an order of magnitude more throughput and lower latency than a B200. With Etched ASICs, you can build products that would be impossible with GPUs, like real-time video generation models and extremely deep & parallel chain-of-thought reasoning agents.
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How We’re Different Etched believes in the Bitter Lesson. We think most of the progress in the AI field has come from using more FLOPs to train and run models, and the best way to get more FLOPs is to build model-specific hardware. Larger and larger training runs encourage companies to consolidate around fewer model architectures, which creates a market for single-model ASICs.
We are a fully in-person team in West San Jose, and greatly value engineering skills. We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both as needed.
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