Nebius will be a TRILLION dollar company. Most people look at Nebius and see a GPU rental business. Roman Chernin just explained on the Q1 2026 earnings call exactly why that framing is wrong and why it misses the most important thing happening inside this company. His argument starts with a simple observation taht in 2026, every product you build requires tokens. You can get tokens from Anthropic, OpenAI, or Gemini and it just works. You call the API, you get intelligence, you ship the product and the moment you want to use open-source models, DeepSeek, Llama, Kimi, Minimax, Qwen, the hundreds of specialized models being released by what Chernin calls neo labs the experience breaks completely. Then you can download the weights from Hugging Face and find an open-source inference engine "but the reality is it will not work. Or at least it will not work at scale or it will not work at scale with the economics you expect. Or it will not work at scale with economics and reliability combined." That is the problem Token Factory was built to solve and it is a $100 billion problem hiding in plain sight. Token Factory is Nebius's production inference platform that brings fine tuning, optimization, orchestration, and deployment of open source and custom models into a single governed system, sub-second latency, autoscaling throughput, 99.9% uptime, and SOC 2 Type II security, even for workloads exceeding hundreds of millions of requests per minute. Early adopters have reported up to 26x cost reductions compared to proprietary frontier models at identical quality levels meaning the same intelligence, at a fraction of the spend. In Q1, Nebius made three acquisitions that each attack a different layer of the Token Factory stack. Tavily brings agentic web search and retrieval, Eigen AI brings advanced model optimization that Nebius paid $643 million to acquire, and Clarifai brings production-grade inference for multimodal and computer vision workloads. Together they turn Token Factory from an inference platform into a complete agentic AI deployment stack, the full pipeline from raw model weights to production AI product, owned and operated by Nebius. The Q1 numbers underneath this strategy are not gradual but rather vertical. Revenue hit $399 million, up 684% year over year. AI-specific revenue grew 841% to $390 million and now represents 98% of total revenue. ARR grew 674% year-over-year, full-year ARR guidance was raised to $7-9 billion with revenue guidance of $3.0-3.4 billion. Adjusted EBITDA margins in the AI cloud segment nearly doubled quarter on quarter to 45%, a company simultaneously growing triple digits and expanding margins, which is essentially unheard of. The power moat sits underneath all of it. Contracted capacity now exceeds 3.5 gigawatts, the company hit its full year target in Q1 and raised guidance to 4 gigawatts by year-end. A new 1.2 gigawatt Pennsylvania AI factory brings total owned sites above 100 megawatts to seven across two continents. A basic GPU rental business sells you access to hardware. Nebius is building the operating system for the open source AI economy, the full stack that turns raw model weights into production intelligence at a fraction of what frontier APIs cost, with the power secured and the infrastructure built before anyone else had the foresight to see it coming. Milk Road Pro remains massively bullish on Nebius and we called it early, we are up huge on the position, and we continue to track every development in AI infrastructure before it becomes obvious to the rest of the market. Come join us at the link in bio/below.

The AI infra trade is a moving bottleneck story. Markets already rerated GPUs, HBM, packaging, memory, CPUs, ... Think early $NVDA and more recently $MU, $SNDK or $AMD. The question is: Will those trades keep on giving? Maybe! In my view though, there are more underappreciated layers further out. As AI racks get energy denser and move toward 800V DC architectures, things like electrical infra, power semis, and speciality materials become interesting. What we have to realize is that the market finds new constraints, rerates them, then moves on. That's where the massive opportunity sits!

Nebius will be a TRILLION dollar company and here is exactly why (Save this). Brad Gerstner's Altimeter just said on camera that they are invested in ClickHouse, and explained exactly why in one sentence: "If you're in the data infrastructure layer, then token consumption is driving a lot more consumption of your basic services." The flip side of that point is equally important. Gerstner added that the closer you are to a point solution, a single use app built on top of AI, "that feels like you're on the front of the conveyor belt heading toward the guillotine." Models get better, apps get commoditized and the companies that own the foundational infrastructure that every AI application must run through keep compounding. ClickHouse is exactly that foundational layer. It is a real time analytical database engine originally built inside Yandex, optimized for the exact query patterns that AI agents, LLM observability pipelines, and machine learning infrastructure generate, massive write volumes, complex aggregations, and sub-second response at scale. It processes hundreds of billions of rows per second, serves over 2,000 enterprise customers including Cloudflare, Uber and ByteDance, and grew 300% in a single year. In January 2026, a $400 million Series D valued ClickHouse at $15 billion more than double its $6 billion valuation just eight months prior. Here is where Nebius comes in. Nebius holds a 28% stake in ClickHouse, an asset that traces back to its Yandex origins. At ClickHouse's current $15 billion valuation, that stake is worth approximately $4.2 billion, sitting largely unrecognized on Nebius's balance sheet while most market coverage focuses entirely on the AI cloud business. A ClickHouse IPO, which the company is actively positioning toward, would force the market to mark that position to full public market value for the first time and could alone reprice Nebius meaningfully. But that hidden asset is just one layer of the bull case. The core AI cloud business just printed 684% year over year revenue growth, $399 million in Q1 2026 against $50 million a year prior. AI specific revenue grew 841% and now represents 98% of total revenue. The moat underneath those numbers is 3.5 gigawatts of secured power capacity, a $27 billion five year contract with Meta, a $2 billion strategic investment from Nvidia, and a Microsoft partnership ramping to full run rate in 2027, all stacked on top of a ClickHouse stake that the market is still not fully pricing in. Milk Road Pro remains massively bullish on Nebius, we called it early, we are up huge on the position, and we continue to track every development across AI infrastructure before it becomes obvious to the rest of the market. Come join us to see our full Nebius thesis and every other position in the portfolio, link below!

Nebius will be a TRILLION dollar company and here is exactly why (Save this). Brad Gerstner's Altimeter just said on camera that they are invested in ClickHouse, and explained exactly why in one sentence: "If you're in the data infrastructure layer, then token consumption is driving a lot more consumption of your basic services." The flip side of that point is equally important. Gerstner added that the closer you are to a point solution, a single use app built on top of AI, "that feels like you're on the front of the conveyor belt heading toward the guillotine." Models get better, apps get commoditized and the companies that own the foundational infrastructure that every AI application must run through keep compounding. ClickHouse is exactly that foundational layer. It is a real time analytical database engine originally built inside Yandex, optimized for the exact query patterns that AI agents, LLM observability pipelines, and machine learning infrastructure generate, massive write volumes, complex aggregations, and sub-second response at scale. It processes hundreds of billions of rows per second, serves over 2,000 enterprise customers including Cloudflare, Uber and ByteDance, and grew 300% in a single year. In January 2026, a $400 million Series D valued ClickHouse at $15 billion more than double its $6 billion valuation just eight months prior. Here is where Nebius comes in. Nebius holds a 28% stake in ClickHouse, an asset that traces back to its Yandex origins. At ClickHouse's current $15 billion valuation, that stake is worth approximately $4.2 billion, sitting largely unrecognized on Nebius's balance sheet while most market coverage focuses entirely on the AI cloud business. A ClickHouse IPO, which the company is actively positioning toward, would force the market to mark that position to full public market value for the first time and could alone reprice Nebius meaningfully. But that hidden asset is just one layer of the bull case. The core AI cloud business just printed 684% year over year revenue growth, $399 million in Q1 2026 against $50 million a year prior. AI specific revenue grew 841% and now represents 98% of total revenue. The moat underneath those numbers is 3.5 gigawatts of secured power capacity, a $27 billion five year contract with Meta, a $2 billion strategic investment from Nvidia, and a Microsoft partnership ramping to full run rate in 2027, all stacked on top of a ClickHouse stake that the market is still not fully pricing in. Milk Road Pro remains massively bullish on Nebius, we called it early, we are up huge on the position, and we continue to track every development across AI infrastructure before it becomes obvious to the rest of the market. Come join us to see our full Nebius thesis and every other position in the portfolio, link below!

Jensen Huang is angry and the numbers explain exactly why (Save this). This clip is his response to two specific arguments that have been used to justify restricting Nvidia's access to global markets and he is not being diplomatic about either of them. The first argument he calls stupid is that GPUs are comparable to atomic bombs. His rebuttal is that there are a billion people using Nvidia GPUs right now, they are inside every medical imaging system on the planet, they were used in the CT scan he got the day before this interview, and he advocates them to his own family. You cannot make that statement about atomic bombs, and the moment you accept the analogy, Huang says, you cannot finish any coherent thought that follows from it. The second argument he calls completely ridiculous: that American companies should not compete internationally because they will lose anyway. His response is the one that landed, "If you guys all apply that same philosophy, why wake up in the morning?" It sounds like a motivational line, but it is actually a specific policy argument that maps onto a catastrophic real-world outcome that has already partially occurred. Nvidia's share of the AI accelerator market in China went from 95% to zero. Because US export controls made it impossible for Nvidia to sell, and by the time Washington partially reversed course and approved H200 exports, Beijing had already launched security investigations into those chips, DeepSeek had announced a pivot to Huawei hardware, and Chinese customers had begun rebuilding their pipelines around domestic alternatives. China represents what Huang called a $50 billion market opportunity. Nvidia has now walked away from $15 billion in lost sales, took a $5.5 billion inventory write-down in a single quarter when the H20 ban hit, and projected an $8 billion revenue loss in the subsequent quarter, all while the market it was excluded from accelerated its own chip ecosystem in direct response to being cut off. Huang's point is not that national security does not matter. His point is that the defeatist logic, "you're going to lose it anyway, so why compete" is self-fulfilling in a way that pure restriction advocates never account for. Every restriction that pushes China toward technological self-reliance is a restriction that permanently reduces American leverage, permanently shrinks American market opportunity, and permanently accelerates the development of the exact domestic alternatives the policy was meant to prevent. And Nvidia, with a $5.4 trillion market cap and zero percent China revenue, is the most visible proof of what that trade-off actually costs.

This is WILD! MIT just solved one of the hardest unsolved problems in robotics (Save this). For decades, the fundamental problem with soft robots and wearable exoskeletons has not been compute or AI, it has been actuation. The moment you try to give a soft robot meaningful strength, you run into the same wall every engineer has hit since the field began, fluid-driven systems require external pumps, hydraulic reservoirs, and heavy infrastructure that makes the entire thing impractical to wear or embed into fabric. MIT's new Electrofluidic Fiber Muscles solve that problem by eliminating external infrastructure entirely. The key insight is electrohydrodynamic pumping using electric fields to generate pressure directly from electricity, with no moving parts, no motors, and no external fluid reservoir. The fibers are less than 2 millimeters thick, can be woven into fabric like ordinary textile, and operate in complete silence because nothing physically moves inside them, it is just ions propelling fluid through a closed circuit. The performance numbers published in Science Robotics are not conceptual, they are empirical results from actual hardware. These fibers achieve a power density of 50 watts per kilogram, matching skeletal muscle, with a contraction strain of 20% and a response time of 0.3 seconds. A single bundled configuration lifted 4 kilograms, 200 times its own weight while a separate configuration drove a robotic arm through a 40-degree bend compliant enough to safely complete a human handshake. Another configuration launched objects in under 100 milliseconds, which is faster than a human flinch reflex. The design mirrors biological muscle architecture in a way that prior artificial muscle approaches never achieved. The fibers are organized into antagonistic pairs, one contracts while the other extends, exactly like biceps and triceps and because the system runs in a closed loop, the relaxing fiber serves as the fluid reservoir for the contracting one, which is what allows the whole system to operate untethered with no external tank. The applications are not hypothetical but rather are the exact use cases the industry has been waiting years for the hardware to catch up to. Exoskeletons for physical labor, prosthetic limbs that move with the natural compliance of biological tissue, assistive garments for patients with motor disorders, and soft robots capable of safe physical contact with humans are all immediately unlocked by a muscle technology that is silent, lightweight, and weavable into clothing. The deeper significance is what this technology does when it meets the AI robotics wave that is already underway. Every major humanoid robot program, Figure, 1X, Boston Dynamics, Tesla Optimus is currently bottlenecked by the same hardware limitations these fibers address, actuators that are too rigid, too loud, too heavy, or too dependent on infrastructure to operate naturally alongside humans. Electrofluidic fiber muscles do not just solve a materials science problem but rather they remove one of the last physical barriers between robots that live in labs and robots that live in the world.

Jensen Huang is angry and the numbers explain exactly why (Save this). This clip is his response to two specific arguments that have been used to justify restricting Nvidia's access to global markets and he is not being diplomatic about either of them. The first argument he calls stupid is that GPUs are comparable to atomic bombs. His rebuttal is that there are a billion people using Nvidia GPUs right now, they are inside every medical imaging system on the planet, they were used in the CT scan he got the day before this interview, and he advocates them to his own family. You cannot make that statement about atomic bombs, and the moment you accept the analogy, Huang says, you cannot finish any coherent thought that follows from it. The second argument he calls completely ridiculous: that American companies should not compete internationally because they will lose anyway. His response is the one that landed, "If you guys all apply that same philosophy, why wake up in the morning?" It sounds like a motivational line, but it is actually a specific policy argument that maps onto a catastrophic real-world outcome that has already partially occurred. Nvidia's share of the AI accelerator market in China went from 95% to zero. Because US export controls made it impossible for Nvidia to sell, and by the time Washington partially reversed course and approved H200 exports, Beijing had already launched security investigations into those chips, DeepSeek had announced a pivot to Huawei hardware, and Chinese customers had begun rebuilding their pipelines around domestic alternatives. China represents what Huang called a $50 billion market opportunity. Nvidia has now walked away from $15 billion in lost sales, took a $5.5 billion inventory write-down in a single quarter when the H20 ban hit, and projected an $8 billion revenue loss in the subsequent quarter, all while the market it was excluded from accelerated its own chip ecosystem in direct response to being cut off. Huang's point is not that national security does not matter. His point is that the defeatist logic, "you're going to lose it anyway, so why compete" is self-fulfilling in a way that pure restriction advocates never account for. Every restriction that pushes China toward technological self-reliance is a restriction that permanently reduces American leverage, permanently shrinks American market opportunity, and permanently accelerates the development of the exact domestic alternatives the policy was meant to prevent. And Nvidia, with a $5.4 trillion market cap and zero percent China revenue, is the most visible proof of what that trade-off actually costs.

Anthropic admitted they built an AI so capable they were scared to release it and the number that explains why is 250. Anthropic's CFO Krishna Rao described in this clip what happened when they ran Mythos against an open source codebase that a previous frontier model had already analyzed. The prior model found 22 security vulnerabilities, Mythos found 250. In the same codebase, that the previous model had already reviewed and flagged as relatively clean. That number, more than 11 times as many vulnerabilities discovered is not just a benchmark improvement, it is a signal that there is an entire layer of software infrastructure that humanity has been operating under the assumption was secure and that assumption may no longer hold. The UK AI Security Institute independently evaluated Mythos Preview and confirmed what the internal numbers suggested. On expert level capture the flag challenges that no model could complete before April 2025, Mythos succeeded 73% of the time and it became the first model ever to complete a complex end-to-end attack range from start to finish, autonomously, without human guidance. The World Economic Forum called this a new security-driven era for AI, the Governor of the Bank of England publicly warned that Anthropic may have found a way to unlock the entire cyber-risk landscape, and the European Central Bank began quietly contacting financial institutions to assess their security posture. The response from Anthropic is what makes this story genuinely important. Rather than shelving the model or publishing it as a standard API release, Rao described a phased approach restricting access to a controlled group, focusing specifically on how the cyber capabilities can be used defensively rather than offensively and treating that framework as a template for how to release powerful but dangerous models in the future. The broader context makes that framing even more significant. AI generated code is already creating ten times more security vulnerabilities than human-written code, 63% of organizations reported experiencing an AI driven cyberattack in the past 12 months, and traditional signature-based security tools were built for a threat model that no longer describes the attack surface companies are defending against. Mythos represents a genuine leap in what autonomous security reasoning can do and it cuts both ways. The model that can find 250 vulnerabilities in a codebase a prior model rated as mostly clean is also, in the wrong hands, the model that can exploit those 250 vulnerabilities before a human defender has even finished reading the report. Anthropic's phased release strategy is not just a legal or PR decision, it is the most honest signal yet from a frontier lab that safety governance and capability development can no longer be treated as separate workstreams. The question is not whether this technology gets deployed, it is whether the institutions using it defensively stay ahead of the ones who will eventually use it offensively and whether the labs building it can keep those two timelines from inverting.

Jensen Huang just told you exactly which AI bottleneck never goes away and it points directly to one of the best trades in the market right now. He did not say chip bottlenecks are permanent. He said the opposite, more chip capacity is a two to three year problem, more CoWoS packaging capacity is a two to three year problem, and none of the manufacturing constraints currently limiting Nvidia's ability to ship are structural barriers that cannot be solved. What he said is permanent or at least, far harder to solve is energy. You cannot build AI factories, reindustrialize the United States or build robots and next-generation compute without energy and energy does not respond to large purchase orders the way foundry capacity does. It involves regulatory timelines, grid interconnection queues, permitting cycles, and national policy decisions that no single company can accelerate regardless of how much capital they deploy. The US is staring down a 19 gigawatt power gap by 2028, and PJM launched an emergency integration plan earlier this year just to handle current data center load, not future load, current load. Nearly half of the data centers planned for 2026 are already delayed or canceled not because of chip shortages but because of transformer shortages, switchgear backlogs and grid capacity constraints that have nothing to do with silicon. This is the exact environment that makes Nebius a structurally differentiated position. While every other AI cloud buildout is fighting the same power bottleneck Jensen described, Nebius has already secured over 2 gigawatts of contracted power capacity with a 1.2 gigawatt campus in Missouri, another 310 megawatts in Finland and a Pennsylvania site adding another 1.2 gigawatts to the pipeline. Power is the constraint Jensen says no one can shortcut and Nebius has already locked in more of it than almost any independent AI cloud operator on the planet. That power moat sits underneath a $27 billion contracted revenue deal with Meta, a Microsoft partnership ramping to full run rate in 2027, and a 684% year over year revenue growth number that just printed in Q1. The Nebius thesis was always about infrastructure scarcity in a world of accelerating demand, Jensen just confirmed on camera which scarcity actually matters long-term, and it is exactly the one Nebius spent the last two years solving before anyone else was paying attention. Milk Road Pro called Nebius early, has been sitting on a massive gain on the position, and continues to track the infrastructure plays that matter before they become obvious to the rest of the market, come join us at the link in bio/below!

Jensen Huang just told you exactly which AI bottleneck never goes away and it points directly to one of the best trades in the market right now. He did not say chip bottlenecks are permanent. He said the opposite, more chip capacity is a two to three year problem, more CoWoS packaging capacity is a two to three year problem, and none of the manufacturing constraints currently limiting Nvidia's ability to ship are structural barriers that cannot be solved. What he said is permanent or at least, far harder to solve is energy. You cannot build AI factories, reindustrialize the United States or build robots and next-generation compute without energy and energy does not respond to large purchase orders the way foundry capacity does. It involves regulatory timelines, grid interconnection queues, permitting cycles, and national policy decisions that no single company can accelerate regardless of how much capital they deploy. The US is staring down a 19 gigawatt power gap by 2028, and PJM launched an emergency integration plan earlier this year just to handle current data center load, not future load, current load. Nearly half of the data centers planned for 2026 are already delayed or canceled not because of chip shortages but because of transformer shortages, switchgear backlogs and grid capacity constraints that have nothing to do with silicon. This is the exact environment that makes Nebius a structurally differentiated position. While every other AI cloud buildout is fighting the same power bottleneck Jensen described, Nebius has already secured over 2 gigawatts of contracted power capacity with a 1.2 gigawatt campus in Missouri, another 310 megawatts in Finland and a Pennsylvania site adding another 1.2 gigawatts to the pipeline. Power is the constraint Jensen says no one can shortcut and Nebius has already locked in more of it than almost any independent AI cloud operator on the planet. That power moat sits underneath a $27 billion contracted revenue deal with Meta, a Microsoft partnership ramping to full run rate in 2027, and a 684% year over year revenue growth number that just printed in Q1. The Nebius thesis was always about infrastructure scarcity in a world of accelerating demand, Jensen just confirmed on camera which scarcity actually matters long-term, and it is exactly the one Nebius spent the last two years solving before anyone else was paying attention. Milk Road Pro called Nebius early, has been sitting on a massive gain on the position, and continues to track the infrastructure plays that matter before they become obvious to the rest of the market, come join us at the link in bio/below!

I believe the current AI bull run looks closer to 1996 rather than 1999 or 2000 there's potential for this bull market to go a lot longer than I think most people are thinking of course, there will be pullbacks and volatility along the way but this build out is only just getting started same with the use cases we see from AI Agents, robotaxis, humanoidrobots, etc. it's still early days

This is WILD! MIT just solved one of the hardest unsolved problems in robotics (Save this). For decades, the fundamental problem with soft robots and wearable exoskeletons has not been compute or AI, it has been actuation. The moment you try to give a soft robot meaningful strength, you run into the same wall every engineer has hit since the field began, fluid-driven systems require external pumps, hydraulic reservoirs, and heavy infrastructure that makes the entire thing impractical to wear or embed into fabric. MIT's new Electrofluidic Fiber Muscles solve that problem by eliminating external infrastructure entirely. The key insight is electrohydrodynamic pumping using electric fields to generate pressure directly from electricity, with no moving parts, no motors, and no external fluid reservoir. The fibers are less than 2 millimeters thick, can be woven into fabric like ordinary textile, and operate in complete silence because nothing physically moves inside them, it is just ions propelling fluid through a closed circuit. The performance numbers published in Science Robotics are not conceptual, they are empirical results from actual hardware. These fibers achieve a power density of 50 watts per kilogram, matching skeletal muscle, with a contraction strain of 20% and a response time of 0.3 seconds. A single bundled configuration lifted 4 kilograms, 200 times its own weight while a separate configuration drove a robotic arm through a 40-degree bend compliant enough to safely complete a human handshake. Another configuration launched objects in under 100 milliseconds, which is faster than a human flinch reflex. The design mirrors biological muscle architecture in a way that prior artificial muscle approaches never achieved. The fibers are organized into antagonistic pairs, one contracts while the other extends, exactly like biceps and triceps and because the system runs in a closed loop, the relaxing fiber serves as the fluid reservoir for the contracting one, which is what allows the whole system to operate untethered with no external tank. The applications are not hypothetical but rather are the exact use cases the industry has been waiting years for the hardware to catch up to. Exoskeletons for physical labor, prosthetic limbs that move with the natural compliance of biological tissue, assistive garments for patients with motor disorders, and soft robots capable of safe physical contact with humans are all immediately unlocked by a muscle technology that is silent, lightweight, and weavable into clothing. The deeper significance is what this technology does when it meets the AI robotics wave that is already underway. Every major humanoid robot program, Figure, 1X, Boston Dynamics, Tesla Optimus is currently bottlenecked by the same hardware limitations these fibers address, actuators that are too rigid, too loud, too heavy, or too dependent on infrastructure to operate naturally alongside humans. Electrofluidic fiber muscles do not just solve a materials science problem but rather they remove one of the last physical barriers between robots that live in labs and robots that live in the world.

I joined Taking Stock on @FINTECHTVglobal to share my thoughts on Memory stocks and the AI infrastructure build out the tl;dr i think we're going higher for longer the demand is real and I don't think its stopping anytime soon the bull market lives on

Nebius is going to be a Trillion-dollar company! Twelve months ago, Nebius was trading near $18 per share with roughly $55 million in quarterly revenue. Today the stock trades above $225, quarterly revenue just came in at $399 million, up 684% year over year and the company has a contracted revenue backlog that would make most Fortune 500 companies envious. But the current market cap, sitting around $56 billion, prices in almost none of what is actually coming. The first reason Nebius reaches a trillion is the Meta deal alone. In March, Nebius signed a five year agreement with Meta worth up to $27 billion, one of the largest infrastructure contracts Meta has ever signed with any company under which Nebius will provide $12 billion in dedicated AI capacity across multiple locations, with Meta also having committed to purchase up to an additional $15 billion in third-party capacity over the same period. That contract barely starts until 2027, which means the revenue impact is not yet reflected in any trailing metric. The second reason is Microsoft, which is currently receiving its first deployment phases from Nebius and is expected to contribute at full annual run rate starting in 2027. Between Meta and Microsoft alone, Nebius has signed agreements worth more than $46 billion in total contracted value before a single additional customer is counted. The third reason is the ARR trajectory, which is the fastest revenue ramp of any infrastructure company in the public markets. Nebius ended 2025 at $1.25 billion in ARR and is guiding to $7–9 billion ARR by year-end 2026. Wall Street analysts project revenue growing 523% in 2026 and another 206% in 2027. One of the company's own institutional shareholders has already suggested the year-end ARR could come in more than twice the guided range if the Meta and Microsoft ramps hit their timelines. The fourth reason is Nvidia's direct involvement. Nvidia made a $2 billion strategic equity investment in Nebius and has given Nebius early access to the Vera Rubin platform, its next generation GPU architecture as part of the delivery commitments to Meta. The fifth reason is the capacity buildout, which is being funded by the revenue itself. Nebius invested $2.5 billion in capex in Q1 alone, CEO Arkady Volozh has guided for $16–20 billion in total investment for 2026, and contracted capacity is now on track to exceed 4 GW by year end with new owned sites in Pennsylvania at 1.2 GW and Finland at 310 MW now under development. The more capacity they build, the more they can sell and demand continues to outpace supply at every stage of the buildout. When you run the math on a business with $7–9 billion in ARR exiting 2026, a $27 billion Meta contract that begins in earnest in 2027, a Microsoft relationship at full run rate, 206% analyst projected growth in 2027, and a structural relationship with Nvidia that gives it hardware access no competitor can match, a trillion-dollar valuation within three to four years is not a moonshot. It is the base case if the compounding holds, and every data point so far suggests it is. Milk Road Pro called this one early. Our analysts added Nebius to the portfolio when it was still flying under the radar, and we are sitting on a massive gain on that position right now. If you want to see what else we are building conviction on before the rest of the market catches up, come join us at Milk Road Pro at the link in bio/below!

The man who built the foundation of modern AI just issued a chilling warning about its future. If you aren't losing sleep after this 47 minute lecture, you haven't realized what's coming. Bookmark this now, you need to understand where the world is actually headed.

Nebius is going to be a Trillion-dollar company! Twelve months ago, Nebius was trading near $18 per share with roughly $55 million in quarterly revenue. Today the stock trades above $225, quarterly revenue just came in at $399 million, up 684% year over year and the company has a contracted revenue backlog that would make most Fortune 500 companies envious. But the current market cap, sitting around $56 billion, prices in almost none of what is actually coming. The first reason Nebius reaches a trillion is the Meta deal alone. In March, Nebius signed a five year agreement with Meta worth up to $27 billion, one of the largest infrastructure contracts Meta has ever signed with any company under which Nebius will provide $12 billion in dedicated AI capacity across multiple locations, with Meta also having committed to purchase up to an additional $15 billion in third-party capacity over the same period. That contract barely starts until 2027, which means the revenue impact is not yet reflected in any trailing metric. The second reason is Microsoft, which is currently receiving its first deployment phases from Nebius and is expected to contribute at full annual run rate starting in 2027. Between Meta and Microsoft alone, Nebius has signed agreements worth more than $46 billion in total contracted value before a single additional customer is counted. The third reason is the ARR trajectory, which is the fastest revenue ramp of any infrastructure company in the public markets. Nebius ended 2025 at $1.25 billion in ARR and is guiding to $7–9 billion ARR by year-end 2026. Wall Street analysts project revenue growing 523% in 2026 and another 206% in 2027. One of the company's own institutional shareholders has already suggested the year-end ARR could come in more than twice the guided range if the Meta and Microsoft ramps hit their timelines. The fourth reason is Nvidia's direct involvement. Nvidia made a $2 billion strategic equity investment in Nebius and has given Nebius early access to the Vera Rubin platform, its next generation GPU architecture as part of the delivery commitments to Meta. The fifth reason is the capacity buildout, which is being funded by the revenue itself. Nebius invested $2.5 billion in capex in Q1 alone, CEO Arkady Volozh has guided for $16–20 billion in total investment for 2026, and contracted capacity is now on track to exceed 4 GW by year end with new owned sites in Pennsylvania at 1.2 GW and Finland at 310 MW now under development. The more capacity they build, the more they can sell and demand continues to outpace supply at every stage of the buildout. When you run the math on a business with $7–9 billion in ARR exiting 2026, a $27 billion Meta contract that begins in earnest in 2027, a Microsoft relationship at full run rate, 206% analyst projected growth in 2027, and a structural relationship with Nvidia that gives it hardware access no competitor can match, a trillion-dollar valuation within three to four years is not a moonshot. It is the base case if the compounding holds, and every data point so far suggests it is. Milk Road Pro called this one early. Our analysts added Nebius to the portfolio when it was still flying under the radar, and we are sitting on a massive gain on that position right now. If you want to see what else we are building conviction on before the rest of the market catches up, come join us at Milk Road Pro at the link in bio/below!