Etched
NativePrivateUpdated November 3, 2026Inference chips built for transformers: the Sohu ASIC runs one model architecture far faster than general-purpose GPUs.
- Website
- www.etched.com
- CEO
- Gavin Uberti
- Founded
- 2022
- HQ
- San Jose, United States
- Total Funding
- $1.6B
- Employees
- 201-500
Products & Offerings
Frontier Inference Cluster
Liquid-cooled rack-scale inference system combining Etched chips, memory, networking and software, which Etched says runs dense, MoE and state-space models.
Sohu
Etched's first-generation inference chip on TSMC N4P, originally designed to run only transformer models, with 144GB of HBM3E.
Low Voltage Inference (LVI) prefill chip
Compute chip that runs at low voltage to fit more transistors without overheating, speeding up the prompt-processing (prefill) stage.
Cluster Scale Memory (CSM)
Proprietary memory and interconnect that lets many chips share one fast, low-latency memory pool for the token-generation (decode) stage.
Executive Summary
What they do
- Designs complete rack-scale AI inference systems it calls frontier inference clusters
- Builds custom silicon on TSMC N4P, including the original Sohu chip
- Splits inference into a low-voltage prefill chip and Cluster Scale Memory decode
Why it matters
- A credible alternative to Nvidia GPUs for high-volume AI model serving
- Reports over $1B in contracts and a first rack running at Jane Street
- Raised about $1B in summer 2026 at a $21B valuation; reportedly fielding offers above $40B
Best fit
- AI labs and model providers whose costs are dominated by inference
- Cloud and neocloud providers looking for more compute supply beyond Nvidia GPUs
- Latency-sensitive operators like trading firms running large models at scale
Watch-outs
- No independent public benchmarks yet; speed claims come from Etched
- Only one production customer publicly confirmed so far, Jane Street
- Inference only; no support for training or fine-tuning workloads
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Etched has working silicon, a first production rack running at Jane Street, more than $1B in reported contracts and very large funding, so its technology is real. Its performance claims have not been independently verified, volume manufacturing is just starting, and it has only one public customer. Most buyers should watch for third-party benchmarks and more customer references. Large-scale inference operators that can run liquid-cooled racks could start early technical talks now.
Signal Provenance
Latest observation date and source for each signal category
| Signal Category | Last Updated | Source |
|---|---|---|
Funding Signals Last funding round, Funding stage | Oct 29, 2026 | Montclare research agents |
Hiring Velocity Headcount, Headcount growth | Nov 3, 2026 | Montclare research agents |
Technical Output Research papers, GitHub activity | Nov 3, 2026 | Montclare research agents |
News Sentiment News mentions, News sentiment | Nov 3, 2026 | Montclare research agents |
Partnership Signals Enterprise partnerships, Distribution partners | Nov 3, 2026 | Montclare research agents |
Revenue Indicators ARR estimate, Revenue growth | Nov 3, 2026 | Montclare research agents |
Leadership Signals CEO tenure, Founder-led | Nov 3, 2026 | Montclare research agents |
Competitive Position Category rank, Market share | Nov 3, 2026 | Montclare research agents |
Why this Bluescore?
6 dimensions, each scored 0–10 against all — companies. Each adds its weight × score to the Bluescore — see methodology