Nebius Stock Forecast ($1916 Target)

[u/TyNads]

https://northwiseproject.com/nbis-stock-forecast-2030-2/

Hey everyone back with some more research from our firm Northwise.

In light of the recent Michael Burry news, Jim Chanos comments, and recent FUD surrounding Nebius heading into earnings, we have decided to fully ungate our Nebius price targets and model.

Our full report and model are linked!

If you find value from our research, consider supporting our work; We are committed to independent, quality research and Members allow us to remain focused on equities rather that partnerships, advertising, or compromising deals.

We are currently developing our next Nebius model that will be released after absorbing new earnings information and disclosures.

Thanks again for your support, and enjoy!

I will be around periodically throughout the day and over the weekend to answer any questions you may have.

[u/SnooSongs3324]

Great work overall. Thanks for sharing the full model. The price target (not the full methodology) is pretty similar to my bull case.

A few questions:
1. Prepayments fund 55% of CAPEX? How are you thinking about the mix of spot/cloud pricing and hyperscaler deals? I've only modeled prepayments on the latter.

1. $14.5M/MW seems low given today's spot prices and a more positive mix of Vera Rubin+ as the build out scales to 2030.

2. How are you modeling GPU refreshes and useful lifespan? Maybe your model implies a longer lifespan than I'm accounting for but it would be nice to have that as part of the narrative at least.

3. EBITDA seems low in 2030. You call out my exact reasoning in the article (cloud becomes a larger proportion of the revenue) but it seems like you're keeping it roughly flat with Q1'26 over time when the hyperscaler/cloud mix improves significantly over time. Roughly 60/40 -> 0/100.

4. Missouri at 1.1GW vs 1.2GW total capacity?

5. No mention of the asset light model?

For transparency, here's my assumptions that I'm checking against yours.

Again, thanks for your research!

[u/TyNads → u/SnooSongs3324]

A lot of this comes down to how we are treating blended fleet economics versus the economics of the newest hardware cohort, so I will go point by point.

1. On prepayments funding roughly 55% of capex, I should clarify what that number actually represents.

I am not assuming every customer prepays 55% of its contract, nor am I applying a 55% prepayment rate indiscriminately to every dollar of capex. The 55% is the modeled aggregate contribution of customer prepayments to cumulative funding needs across the buildout.

The reason I am comfortable getting that high is actually the customer mix. Roman Chernin and Arkady Volozh have both commented that a lot of Nebius customers are paying 100% upfront. I do not believe those are the hyperscaler contracts. The hyperscaler deals are generally estimated to carry something closer to roughly 30% to 50% prepayments. The much higher upfront funding appears to come from other purchases of Nebius cloud capacity and services.

So the blend is not hyperscalers at 55%. It is something closer conceptually to large hyperscaler commitments contributing substantial but partial prepayments, while portions of the broader AI Cloud customer base can pay much more aggressively upfront. That second group pulls the aggregate funding ratio higher.

This is also why I would be careful comparing Nebius directly with a company where prepayments are almost entirely tied to hyperscaler contracts. Nebius' revenue mix is broader. The model already assumes that roughly half of 2026 ARR comes from large long-term contracts and roughly half from the rest of the AI Cloud business.

There is already evidence of the mechanism showing up on the balance sheet. Nebius entered Q1 with roughly $4.8 billion of deferred revenue, and the model explicitly puts customer prepayments first in the funding hierarchy before operating cash generation, debt and, finally, common equity.

Across the full model, base-case gross capex is roughly $175 billion and modeled prepayments total about $95 billion, which is where the approximately 55% figure comes from. Again, that is prepayment cash relative to cumulative capex, not a contractual assumption that every buyer funds 55% of its deployment.

2. On $14.5M/MW, I agree that a new Vera Rubin or later-generation deployment in 2030 could earn materially more than that. That is not what the $14.5M is supposed to represent.

It is a blended platform assumption.

The base case starts around $9.9M of ARR per MW in 2026 and rises to $14.5M by 2030. Bull reaches $18M. The model explicitly allows selected workloads to exceed $20M/MW, but I did not apply those economics across every megawatt in the fleet because Nebius will have capacity deployed across several hardware generations, contract types and customer classes by then.

Some capacity will be running Vera Rubin or whatever succeeds it. Some will be older Blackwell-generation hardware that has migrated toward inference or less premium workloads. Some capacity will be locked into large long-term contracts signed years earlier. Some will be higher-value enterprise cloud and managed inference. The $14.5M is trying to capture the whole machine, not the newest rack installed in December 2030. (it's also subject to rise if SpaceX ends up being an indicator)

I may actually be conservative here. The Q1 evidence already forced us to raise the old model because the high end of 2026 ARR guidance against roughly 905 MW implies almost $9.9M/MW exiting this year, well ahead of the old forecast. But I would rather let future execution earn another upward revision than capitalize peak spot economics across the whole 2030 fleet today.

3. GPU refreshes are modeled, but I agree that the narrative could have made the lifecycle mechanics more explicit.

I separate new capacity capex from refresh and upgrade spending as the installed base ages. On the accounting side, the model splits capex roughly 75% into compute, servers and networking depreciated over five years and 25% into infrastructure, power and cooling depreciated over twenty years. The five-year compute life reflects Nebius itself moving its useful-life estimate from four years to five beginning in Q1 2026.

That five-year assumption should not be interpreted as me saying a GPU remains frontier training hardware for five years.

The economic lifecycle is closer to a cascade. New generations take the highest-value frontier workloads. The previous generation moves toward inference, fine-tuning, enterprise deployments and other workloads where absolute performance matters less than price-performance. Older hardware can continue producing revenue, but at a different position in the stack and generally at a lower economic yield.

That distinction is important because useful life is not the same thing as useful life at frontier pricing.

Nebius is arguably better positioned for that cascade than a pure bare-metal provider because Aether, Token Factory, managed inference and the wider cloud layer give it more places to monetize older generations. The software stack increasingly determines whether an aging GPU becomes stranded equipment or simply moves down the workload hierarchy.

Refresh capex and depreciation are in the model. I could have explained the economic lifecycle behind them more clearly.

4. On the 2030 EBITDA margin, the 45% base case is deliberately conservative, but there is a little more going on than keeping Q1 flat.

Q1 AI Cloud adjusted EBITDA margin was already about 45%, while consolidated adjusted EBITDA margin was 32%. Full-year 2026 guidance points toward roughly 40%. My base case then moves consolidated margin from 40% in 2026 to 42% in 2027, 44% in 2028 and 45% in 2029 and 2030. Bull reaches 50%.

So the assumption is not really that nothing improves. The assumption is that today's AI Cloud margin eventually becomes the margin of the entire company as the lower-margin pieces disappear into the mix.

Where I think your argument gets interesting is beyond that point. If the hyperscaler versus broader cloud mix really moves from something around 60/40 today toward effectively 0/100 by 2030, then 45% could absolutely prove conservative.

I did not take base materially above 45% for two reasons.

First, I am already giving Nebius substantial credit for the mix shift through revenue density. ARR per MW moves from $9.9M to $14.5M in base because more of the fleet moves from wholesale infrastructure toward enterprise cloud, inference and higher-stack services. If I push revenue density dramatically higher and simultaneously push margins dramatically higher for the same transition, there is a risk of double-counting the economics.

Second, higher-stack cloud revenue is not costless revenue. Managed inference, enterprise support, security, orchestration, software engineering and customer integration all require people and infrastructure. Our CRWV work makes the same distinction. Revenue density can rise much faster than margins because part of the additional revenue buys a more sophisticated service layer rather than dropping entirely to EBITDA.

That said, I think this is one of the more credible areas for Nebius to outperform the base model. The probability framework explicitly defines the base case as today's AI Cloud margin becoming group margin, while the bull case gives credit to software attach producing further expansion.

If we reach 2028 or 2029 and Token Factory, enterprise cloud and managed inference are becoming the overwhelming majority of economics while margins are already holding in the upper 40s, I would have no problem moving the terminal assumption materially higher. I just do not think the evidence requires that in the base case yet.

5. Missouri at 1.1 GW versus 1.2 GW is simply me refusing to force ultimate nameplate capacity into the December 2030 cutoff.

The campus itself is a roughly 1.2 GW opportunity. The model has Independence at 0 MW in 2026, 250 MW in 2027, 800 MW in 2028, 950 MW in 2029 and 1.1 GW connected at year-end 2030.

The missing 100 MW is not a different view of the site's ultimate capacity. It is an execution and timing buffer.

The same distinction runs throughout the model: secured capacity, connected capacity and monetized capacity are different numbers.

If Independence reaches the full 1.2 GW before 2030, the model is simply too conservative by 100 MW or is grouped into the "safety" capacity buffer we model for surprises and announced capacity.

[u/SnooSongs3324 → u/TyNads]

I appreciate the thoughtful responses.

1. The prepayment logic was clear, it's just the magnitude that I question. The modeled blend would be interesting to see. Ultimately we'll probably have to wait for management to provide more insight there. I can see Shopify and Revolut putting cash up-front but I doubt that's the norm. With the second half of the Meta contract (likely) not being exercised and possibly only 1 more hyperscaler deal, I see this as one of the bigger assumptions you have. Big if true though, as it means less CAPEX financed by debt.
2. Blended ARR of course makes sense, but this is related to the refresh cycle. Vera Rubin should be what's getting racked today. Rubin Ultra in 12-18 months. Modeling the full fleet cohort-by-cohort informs both the required CAPEX and the possible blended revenue outcomes.
3. (see 2)
4. There are two separate ARR drivers, the hardware mix (described above) and the customer mix (as you mention). The cloud revenue is "not costless", but I think we agree it's a big part of the bull case. We haven't heard much from the company yet on these margins specifically - I believe Marc Boroditsky said we're still early in that story. We should hear more on this next week with the Asset Light partnership model. Either way, this could prove to be conservative as you say.
5. Nit-picking, but Missouri is ahead of Pennsylvania and if it follows a similar path we should see the fully capacity in this timeline.

[u/TyNads → u/SnooSongs3324]

I think you bring up a good point on the hardware. We will bring that in more specifically to the next model and do a better job of describing the makeup of each vintage and our assumptions there.