dylan ツ(@demian_ai):yesterday, our own Arkady (CEO) and Marc (CRO) did a fireside at Goldman’s communacopia + technology conference (a public investor webcast we posted on the IR hub) with super interesting insights about $NBIS here’s what they actually said: -> Demand is still bigger than the industry can build Arkady said it best: AI is creating real value, coding, security, office work, and that demand runs down the stack: models, then compute and cloud, then the buildings and the power. It can grow many times a year, but the physical world cannot. Visibility used to be about 18 months. Now about 24, maybe more. The ask moved further out: orders for q1/q2 2028, including tens of thousands of Vera Rubin gpus. AI is working, but it needs to be served. As an industry we cannot build as fast, and that’s why prices go up. raising the list price didn’t cool anything. It was tried, demand stayed. So the company ran an experimental Blackwell auction a few weeks ago. It came in about 15-20% above any previous price these were sold out, after those raises. The winners were happy because they got capacity they could actually count on. A few more of these will run, including with self-serve customers, and used as a reference when pricing bigger deals. Contracts are being split into three buckets: - short (3-6 months): a small slice, often emergency training runs, higher $ per MW - medium (1-3 years): the core. ai natives, digital natives, early enterprise - long (5+ years): hyperscaler deals, used to help fund the build last-gen GPUs are not scrap Demand is growing faster than supply. That does not only mean people are stuck on old chips, a lot of RAG, text, and image work is just a better fit for hardware they already trust, they know the cost and the reliability. There is even a list of new customers asking for older chips when any come free. Leftover lab capacity is mostly bare metal. Goldman asked about meta selling unused cluster capacity. Arkady’s distinction: Spacex is already selling unused machines as bare metal, to buyers like anthropic, google, azure, who then put a cloud and services on top. meta might do the same. That’s hardware. someone still has to operate it and sell it to the end customer. more of that supply is useful, unused capacity could be taken, packaged, and resold. size check: the market was put around 5-10 gw now, maybe 15-20 gw by 2028. A few extra gw from a lab (Spacex talk was cited around 6-8 gw) is roughly 20-30%. helpful, but not a rewrite of the market. the four large wins from last quarter averaged about $1b each. Those weren’t won on price, they were won in the POC. Those four are already talking about the next cluster (more gb300 in some cases; vera rubin in all cases). the limit is how fast capacity can be built, and how it’s financed. Buildings are one thing. Filling them with gpu racks is tens or hundreds of billions. Owned data centers are the base rate. the newer move is partnering with electricity / data-center companies that already have land, power, and cheaper financing, but not the know-how, racks, software, or customers. capacity from 2027 on. several projects already in motion. on power: ready sites, grid connections, or own generation, including a Bloom partnership that was mentioned. Same stack, further down: software → racks → data centers → sometimes the power itself. Who Nebius sells to The path they described: ai natives → larger ai natives → digital natives → enterprise platforms → enterprises. Platform companies that serve enterprises are showing up wanting capacity plus training, post-training, and inference on one stack. replay is on the investor hub:

2026.09.10 15:25

yesterday, our own Arkady (CEO) and Marc (CRO) did a fireside at Goldman’s communacopia + technology conference (a public investor webcast we posted on the IR hub) with super interesting insights about $NBIS here’s what they actually said: -> Demand is still bigger than the industry can build Arkady said it best: AI is creating real value, coding, security, office work, and that demand runs down the stack: models, then compute and cloud, then the buildings and the power. It can grow many times a year, but the physical world cannot. Visibility used to be about 18 months. Now about 24, maybe more. The ask moved further out: orders for q1/q2 2028, including tens of thousands of Vera Rubin gpus. AI is working, but it needs to be served. As an industry we cannot build as fast, and that’s why prices go up. raising the list price didn’t cool anything. It was tried, demand stayed. So the company ran an experimental Blackwell auction a few weeks ago. It came in about 15-20% above any previous price these were sold out, after those raises. The winners were happy because they got capacity they could actually count on. A few more of these will run, including with self-serve customers, and used as a reference when pricing bigger deals. Contracts are being split into three buckets: - short (3-6 months): a small slice, often emergency training runs, higher $ per MW - medium (1-3 years): the core. ai natives, digital natives, early enterprise - long (5+ years): hyperscaler deals, used to help fund the build last-gen GPUs are not scrap Demand is growing faster than supply. That does not only mean people are stuck on old chips, a lot of RAG, text, and image work is just a better fit for hardware they already trust, they know the cost and the reliability. There is even a list of new customers asking for older chips when any come free. Leftover lab capacity is mostly bare metal. Goldman asked about meta selling unused cluster capacity. Arkady’s distinction: Spacex is already selling unused machines as bare metal, to buyers like anthropic, google, azure, who then put a cloud and services on top. meta might do the same. That’s hardware. someone still has to operate it and sell it to the end customer. more of that supply is useful, unused capacity could be taken, packaged, and resold. size check: the market was put around 5-10 gw now, maybe 15-20 gw by 2028. A few extra gw from a lab (Spacex talk was cited around 6-8 gw) is roughly 20-30%. helpful, but not a rewrite of the market. the four large wins from last quarter averaged about $1b each. Those weren’t won on price, they were won in the POC. Those four are already talking about the next cluster (more gb300 in some cases; vera rubin in all cases). the limit is how fast capacity can be built, and how it’s financed. Buildings are one thing. Filling them with gpu racks is tens or hundreds of billions. Owned data centers are the base rate. the newer move is partnering with electricity / data-center companies that already have land, power, and cheaper financing, but not the know-how, racks, software, or customers. capacity from 2027 on. several projects already in motion. on power: ready sites, grid connections, or own generation, including a Bloom partnership that was mentioned. Same stack, further down: software → racks → data centers → sometimes the power itself. Who Nebius sells to The path they described: ai natives → larger ai natives → digital natives → enterprise platforms → enterprises. Platform companies that serve enterprises are showing up wanting capacity plus training, post-training, and inference on one stack. replay is on the investor hub:

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