Boom! $100m Series A to bring ultrafast inference for open source. We believe the demand for ultrafast inference will be many times larger than slow inference. But right now it's never made it to market at scale. We are here to change it. First racks live in Q1 2027 🚀 Massive thank you to @jamespalmer13 at @BlackbirdVC and @dkwon98 at @abstractvc for co-leading. + participation from @QEDInvestors, @645ventures, @carbideventures, @endeavor_global and @ausgulfcapital, @icehouse_ventures and bold capital partners. Final hat tip to our entire cap table who doubled down. No better feeling as a founder than getting this level of conviction from your existing backers. @maxkilberg, @adwane and @bencasnocha from @villageglobal (pre-seed) @camborumand from @Fuse_vc (seed) @jthassel from evercrest (Seed) @morganschwanke from @manaventures (pre seed) @salil from Uncorrelated Ventures (seed) @themichaelljgo from @plugandplaytc (angel / pre seed) Spicy chips are going mainstream 🌶️ xitter.cf/general_compute/status…

SemiAnalysis numbers imply OpenAI is selling Cerebras-powered Ultrafast inference at ~$200M per megawatt per year. People are re-running the maths hoping for a typo. We're not surprised. A megawatt is a megawatt. What it earns depends on the silicon inside it. Here's how we think about it: Near term, revenue per megawatt wins. Power is the scarcest input in AI, and whoever monetizes each MW best gets the next MW. Long term, gross margin per megawatt wins. Prices compress, competitors arrive, and only the operators with real cost and pricing advantages keep the spread. Cerebras is built for both. Speed is the product. A frontier model at 750 tokens per second is something GPU clouds haven't publicly matched, and customers like Jane Street pay a premium for it. Premium pricing on a contracted, scarce resource is how you protect margin when everyone else is racing to the bottom. That's why we're extremely bullish on Cerebras, and why we're buying as many megawatts as we can. Premium inference unlocks the most delightful user experience in AI. No more waiting, waiting, waiting, staring at little thinking animations while the model works in the background. Answers that keep up with your thoughts. Our customers are even more excited than we are. That's General Compute.

The pace of change in the silicon world is crazy rn A year ago 3 of the 15 inference asic programs we looked at had shipped silicon in volume. Now that number's 9. Each of them have their special sauce or angle. Some compete with Nvidia - some compliment like the memory focussed folks Mini-Cambrian explosion happening and i'm quite sure most of them will be roaring successes Shipping in volume with failure testing, rack scale solutions is where our lenders, not just a VC, can underwrite the growth at scale This year is going to be huge. Next year even huge-er