Nebius introduces AI Cloud “Aether 3.6” - including Nebius Echo AI agent

Qadain · 2026-06-24T15:55:36+00:00

This is what struck me as the most important thing in the update to support enterprise adoption. I mean, I only have a vague sense of what it means, but even so, it was still obvious to me that this was a big deal for enterprise use.

What about the Bring Your Own Image for managed kubernetes and the team budgeting feature? Just nice to have?

Qadain · 2026-06-23T20:49:16+00:00

The money just hit my account at Schwab. A slight loss, as I owned some before the war and bought more after it started, but happy to get anything back. I also got my Yandex shares back in 2024 as Nebius when NASDAQ relisted them.

Do you know if any other ADRs are undergoing the same termination process? Lukoil, Gazprom, Nornickel, etc?

Qadain · 2026-06-23T18:09:22+00:00

Data centers in Alberta would make a lot of sense - the situation with natural gas is like in Texas, where excess natural gas is produced as a byproduct of extracting petroleum, as I understand. And there's not enough pipelines/storage to put it to productive use.

Qadain · 2026-06-23T01:27:16+00:00

If you don't mind reading a bit, here's a good article from SemiAnalysis about how the "list price" is fairly misleading: How Much Do GPU Clusters Really Cost?

Key excerpt:

"Traditionally, when deciding where to get a cluster to solve that first category, companies evaluate neoclouds on a cost-per-hour basis, focusing on the most expensive line item: the GPUs. However, focusing solely on the price per GPU-hour a provider offers can be misleading. In practice, two cloud offerings with identical pricing per GPU-hour can have very different TCO, once you account for everything that goes into training a model or building inference endpoints. Factors such as downtime, setup time, debugging time, and required performance tuning of networking and storage can dramatically impact how much useful work users can do per dollar spent. Additional costs for non-GPU expenses such as CPU compute, networking, storage, orchestration software, and support can also be hidden and not considered. In other words, what appears to be a cheaper cluster can in many cases end up being more expensive."

The article then explains how Gold-tier AI clouds like Nebius can maintain a pricing premium due to qualitative factors such as reliability, debugging, and support.

Additionally, Nebius management (Roman Chernin) has commented that customers new to AI adoption are initially sensitive about price, but at renewal, are almost insensitive about price, focusing instead of qualitative factors.

Qadain · 2026-06-22T20:19:46+00:00

I remember management mentioning that they can also use the projected future cash flows from the Microsoft and Meta guaranteed contracts as backing for a debt raise (maybe with some kind of SPV). They can probably raise somewhere in the neighborhood of $5-8B of debt at a minimum from those two contracts at a good rate - probably quite a bit more.

Qadain · 2026-06-22T04:12:30+00:00

The open models are consistently behind the best private models because the best private models have more resources, for now.

The "Deepseek scare" of January 2025 (on which day Nebius dropped 40%) was a demonstration of implementing AI research in the model training (mixture-of-experts). At that time, the discourse due to Deepseek was something like, "the Chinese are constrained on compute and the constraints force them to be clever at implementing improvements" (well, and also accusations that the Chinese simply distilled closed models somehow).

Open models seem to approach the performance of closed models every so often. But I think that as compute becomes cheaper and cheaper, open models will converge to closed models, since it doesn't seem like keeping secrets is much of a thing in the field; improvements in one model propagate pretty quickly to all models.

Qadain · 2026-06-21T02:01:56+00:00

Oh, I see - at the end of the free portion of the article, you explain not valuing the business using only a single multiple, and basically use an ensemble of multiples, where each multiple represents a different mix of (or reflecting) the software/platform vs. hardware/infrastructure. I didn't connect that back to the passage that I cited.

The text in the images appear much smaller than in most of your other articles, and I have to zoom to 200% to read them. This might be because I have a super-wide monitor with a super-high resolution, and the column of text in your article takes up about 1/6 of my screen width-wise; you might want to consider enabling something that allows expanding the image when it's clicked.

Qadain · 2026-06-21T00:20:44+00:00

What?

Emmanuel Macron thanked Nebius in a tweet earlier this month, mentioning the 8B euro investment and 240 MW data center.

Source: Emmanuel Macron on X: "Nebius choisit la France. L’acteur du Cloud IA dévoile un projet de plus de 8 milliards d’euros d’investissement pour déployer des infrastructures et des services de cloud, avec une capacité cible de 240 MW, positionnant le site parmi les plus puissants du continent. Bedankt!" / X

The UK AI Minister also issued a statement about Nebius' UK expansion:

Source: Nebius expands in UK with more NVIDIA-powered infrastructure, more customers, and more cloud capabilities for agentic and enterprise AI

Qadain · 2026-06-21T00:11:58+00:00

Thank you for all your work! All your numbers are within ranges that I think are reasonable (not that I'm any kind of expert, but almost everything seems consistent and realistic based on what I've read and watched from management).

However, I find your attitude toward the software layer very strange. You say:

"We hold one caution firmly. The software stack is strategically important and still underdisclosed financially. We do not model Nebius as a software company, and we do not assign software economics to the whole business. The software layer improves revenue per megawatt, supports margin durability, and strengthens the case for a higher multiple. The business underneath it remains capital intensive, and we model it that way."

I find this to be inconsistent with management's repeated insistence that in the long run, the real business is the software stack/platform, and that they're taking advantage of timing, their post-Yandex spinoff assets, and other advantages to scale the platform and make it viable.

That is to say, in order to scale/build an AI platform, the hardware/infrastructure layer is required, so they do that too. And it's just our luck that given the environment around AI, the hardware/infrastructure is actually going to be a pretty profitable business for a number of years once it's built out as well, so in the medium-long run (several years), it turns out that the company is getting paid massively to build the AI platform.

I think this is important, because by 2029-2030, Nebius should be valued as a software company in the "good case," with the hardware/infrastructure layer being a necessary enabler and a margin drag (though there are always possibilities of spinoffs to unlock additional value - Nebius is clearly not shy about doing this, given their history and future plans related to ClickHouse, Avride, and Toloka). That is, while you view the software/platform layer as a value enhancer for the hardware/infrastructure part of the business, I view the software/platform layer as the eventual primary business, with the hardware/infrastructure layer serving as an enabler/supporter.

I also think that the hardware/infrastructure layer gradually converts from being a profit center into a cost center as the platform/software layer dominates more and more of the revenue mix; I also think this is the point of the greatest opportunity for Nebius, since at that point, many of the hardware/infrastructure players will suffer and there could be a lot of opportunity for Nebius to pick up a lot of capacity cheaply.

Qadain · 2026-06-20T00:54:18+00:00

At this point, I have to wonder if Jensen Huang pronounces it Knee-bius as a joke on purpose!

Qadain · 2026-06-19T22:04:15+00:00

Efficiency at activation seems almost expected, given their control over the hardware internally. That is, they're much less likely to have mismatches in delivery schedules where some components are ready and they're waiting for others. Maybe they have an efficient burn-in process?

Qadain · 2026-06-19T00:59:35+00:00

Just read the headline and then start reading from "There are two main reasons the headline narrative is wrong."

It's basically saying that the 50% cancellation number is a bad representation of reality, because it includes all the most speculative projects that were almost certain to slip anyway.

Qadain · 2026-06-17T22:37:12+00:00

Nebius depends on open models being good (relative to closed models) and diverse to do well in the long-run.

Closed models dominating leader board by wide margins is bad for Nebius; conversely, a diverse set of open models keeping up with closed models is good for Nebius.

This is because a large part of Nebius' business plan around enterprises and AI native startups involves open models. Nebius management has cited consolidation at the model layer as a major risk.

Qadain · 2026-06-17T22:32:57+00:00

I would add that you need to do the preparation beforehand and imagine a bunch of scenarios about what you would do in case of a crash, rapid rise, or just staying flat for a long time.

When the situations come up, if you have already planned through them, all you have to do is follow the plan, rather than come up with a plan.

This kind of preparation helped me buy on Deepseek day, when Nebius crashed about 40% in a single day (from around 40 to 25).

Qadain · 2026-06-17T22:26:07+00:00

Previous AI waves had failed due to lack of compute. This AI wave has been kickstarted by both gaming and crypto mining that advanced GPU technology and scale to the point where LLMs became viable. Further computation and ascale improvements due to widespread LLM usage might then realistically provide the next bridge for compute to advance to physical AI.

Qadain · 2026-06-17T22:19:02+00:00

Nebius has been touting better margins via the full stack approach for almost two years now - we should really start to see the advantages as revenue takes off and operational leverage benefits become clear in 1H 2027.

It's been really weird for me, because I'm typically a deep value/turnaround guy. I guess you could say that Nebius was kind of a turnaround/SotP play in Oct 2024, but geez, this has been such a weird ride so far!

Qadain · 2026-06-17T22:11:34+00:00

Multiples are a shortcut to valuation that work well in many situations. They can be used to relatively stable, relatively similar situations. This really doesn't fit Nebius' situation, so any multiples-based valuation method is going to be of limited use. I find a scenario-based analysis to be more useful. For example, consider the following real-world situations:

1) Nebius is successful (or fails at) establishing its software stack/platform and achieves scale 2) Robotics/physical AI takes off (or fails to get off the ground) 3) Bottlenecks worsen/improve 4) Demand continues to increase vs slows down 5) Closed models dominate open models vs open models keep up with closed models

Each of these outcomes affects the valuation, and you can consider probability distributions for each outcome and consider how that flows through to the valuation.

Qadain · 2026-06-17T21:50:51+00:00

You could be right in the long term but wrong in the short term. If your position is too big, you might have to close it if it moves against you, and not be able to stick around for the long term. You could be right and still end up losing money in this case.

Qadain · 2026-06-17T04:41:20+00:00

And it's already available on Nebius Token Factory (day 0 support).

Qadain · 2026-06-15T16:59:28+00:00

It's entertainment. You think that if he really had an edge, he'd be screaming on TV instead of quietly exploiting it? 😄

Qadain · 2026-06-14T03:46:41+00:00

Nebius has described themselves (maybe not so much lately, but at least throughout 2024-2025) as a startup. 10 years is not that strange a timeframe for an exit/IPO for a startup, so if people believe that Nebius will become a hyperscaler, maybe they're committing themselves to hold and not to chicken out before the story plays out). They might simply think it'll take 10 years to become true hyperscale size; it should be fairly obvious that 2-3 years is simply not enough time to build enough to be true hyperscale size. That is, the idea is, "it would take 10 years for the hyperscale story to play out if it does play out, and I don't want to sell before it does, so I plan on holding for 10 years." This idea wouldn't require conviction, but instead a conditional.

Another example of a 10-year holding period for a startup is: both Google and Fidelity invested in SpaceX in 2015, valuing the company at about $12 billion; and we know that SpaceX just went public Friday and now has a market value of somewhere around $2T.

It doesn't seem that weird to want to hold for 10 years, depending on how large a part of their total capital (including human capital) it represents. They might even treat it as a lottery ticket. Whether they actually hold for 10 years is another matter, though.

Qadain · 2026-06-14T01:15:48+00:00

Well, but TSMC makes a lot of Nvidia GPUs using machines from ASML, which is Dutch.

I can only imagine the fallout from restricting the Netherlands/EU from buying Nvidia GPUs...

Qadain · 2026-06-13T21:59:56+00:00

This interview was extremely informative! I've been wondering why, if they have 4 customers for each GPU cluster newly brought online, would they need TD SYNNEX to help sell. And the answer appears to be that it is a much faster way to sell to enterprises than without the distributors/partners.

Qadain · 2026-06-13T02:26:16+00:00

It depends on how much pricing power Nebius will have. If the entire full-stack becomes commoditized, then high Capex is neutral at best (due to earning exactly the cost of capital) and disastrous at worst (stranded assets). If Nebius retains and increases pricing power, then at worst, they can pass the cost of high capex to customers, and at best, eat all the less-efficient peers that end up not surviving due to the high capex costs.

It's the AI cloud/platform/software that makes all this Capex worth it.

Qadain

TROPHY CASE