$NBIS (-0,35%) CEO Arkady Volozh and CRO Marc Boroditsky just spoke at the Goldman Sachs Technology Conference.
Here are the key takeaways:
1) Demand continues to accelerate
Nebius made it clear that demand for AI infrastructure continues to far outstrip supply. Importantly, the visibility of future demand continues to extend.
A few months ago, management was still talking about visibility of about 18 months with demand remaining strong. Now Arkady says that this period has extended to 24 months or possibly even longer. Customers are already inquiring about capacity for Q1 and Q2 2028.
He also said that customers are currently requesting tens of thousands of Vera Rubin GPUs.
Marc emphasized this point, noting that demand is not only exceeding supply but is growing faster than supply.
2) Explanation of the Partnership Between Nebius and Palantir
The underlying thesis revolves around enterprise data.
Arkady believes that companies increasingly want to run open-weight models on their own proprietary data. These models are intended to be continuously improved within their respective enterprise domains. At the same time, companies want to retain control over the resulting data and the intelligence gained from it, rather than constantly feeding it back into external commercial models.
Palantir already has the enterprise software layer and the necessary tools to orchestrate such processes. What Palantir lacked was the underlying infrastructure.
This is exactly where Nebius comes in.
“We provide the entire stack, right down to our Token Factory. They take this stack, add their own tools and their customer base. For us, this is an excellent way to gain access to enterprises.”
This could give Nebius access to an enterprise customer base that would have taken considerably longer to build organically.
3) Enterprise demand appears to be reaching a tipping point
The Palantir deal is part of a larger trend.
Marc said Nebius has seen a “significant increase” in its pipeline with platform companies that themselves serve enterprise customers.
Some of these companies view Nebius as their first provider outside of the major hyperscalers. They are not just looking for training capacity, but for a partner that can support training, post-training, and inference across the entire AI lifecycle.
The evolution of customer segments is becoming increasingly clear:
AI Natives → Larger AI Natives → Digital Natives → Enterprise Platforms → Enterprises Themselves
Management continues to believe that enterprise customers will represent the largest portion of the market opportunity.
4) xAI and $META (-0,13%) selling excess capacity
Goldman asked what would happen if companies like xAI and Meta built enormous amounts of infrastructure for their own use and later offered unused capacity on the market.
Arkady explained that this would largely consist of bare-metal capacity rather than a full AI cloud.
Someone would still need to take on this infrastructure, add the cloud and software layers, and then market it to end customers.
Nebius could potentially be one of those companies.
“If they could bring more capacity to the market, that would be good for the industry and good for us. We could take it on, repackage it, and resell it to end customers.”
5) The four major customers are already working on their next clusters
The four major customer wins announced last quarter were not one-time capacity deals.
Marc said that these customers already have additional needs and are discussing their next deployments with Nebius.
In some cases, they are asking for additional GB200 capacity, while all four customers are already discussing requirements for the Vera Rubin platform.
Furthermore, Nebius has other similarly large opportunities in the pipeline.
Important: Marc reiterated that these contracts were not won based on price, but rather on the reliability and performance that Nebius was able to demonstrate during the proof-of-concepts (POCs).
6) Older GPUs remain in demand for a specific reason
This is exactly the point I’ve been highlighting for quite some time.
Marc explained that older GPUs aren’t staying fully utilized simply because customers can’t get newer chips.
Many workloads—including RAG infrastructure, text prediction, and image generation—are actually more cost-effective on older hardware.
With these GPUs, customers already have a very clear understanding of the total cost of ownership (TCO), reliability, and performance.
“We actually have a list of new customers looking for chips from older generations as soon as they become available.”
This is exactly the dynamic I’ve been arguing:
The most powerful GPUs will increasingly be allocated to the most computationally intensive workloads, while older GPU generations remain economically viable when their performance is already more than sufficient for certain applications.
7) The Asset-Light Model Is Gaining Ground
According to Arkady, the asset-light strategy is designed to address two of Nebius’s most significant constraints:
How quickly Nebius can physically build out new capacity.
How much of this expansion Nebius can finance on its own.
The partners Nebius is in talks with are typically power utilities or data center companies that already have land, electricity, and, in some cases, access to affordable financing.
What they often lack is the expertise to move further up the AI infrastructure stack.
Nebius can contribute data center expertise, racks, the software stack, and customer demand to monetize this infrastructure.
Management says there is a long list of companies interested in this model.
Arkady describes each individual line in the internal pipeline as a major project in its own right.
Nebius is already working on several of these projects. The corresponding capacity is expected to come online starting in 2027.
In short: These statements paint a very positive picture for Nebius: strong and steadily rising AI demand, increasing enterprise activity, large follow-on orders, demand even for older GPUs, and an asset-light model that could accelerate capacity expansion.
