Episode summary
How CoreWeave Sees the Market for Compute Right Now | Odd Lots
Odd Lots
· · 51 min · Hosts: Tracy Alloway, Joe Weisenthal · Guests: Brannin McBee
Summary
CoreWeave says demand for AI compute is still running ahead of supply, but the bottleneck has shifted. Brannin McBee argued that the market is no longer just about getting GPUs; it is increasingly about securing powered shells, transformers, backup power, and the labor needed to build and operate data centers. He said CoreWeave is seeing no meaningful pullback in inference demand and that the company is now serving a broader customer base beyond hyperscalers and AI labs.
McBee said the company’s customer mix has diversified materially, with enterprise adoption becoming a bigger part of the business and financial-services clients adding to backlog. He also said AI labs are extending contract durations, moving from three-year commitments to five-year take-or-pay deals, while asking for larger deployments and uninterrupted access to the same infrastructure. In his view, that pattern supports the idea that demand for advanced compute will keep expanding rather than normalizing.
The episode also focused on whether compute can become a tradable commodity. McBee argued that GPU compute is still not fungible enough for a liquid futures market, because performance depends heavily on configuration and operations, not just the chip itself. He said CoreWeave is still overwhelmingly hearing demand for Nvidia infrastructure, even as competitors and customers explore custom silicon and other hardware approaches.
Key takeaways
- Brannin McBee said CoreWeave is seeing broadening demand beyond AI labs and hyperscalers, with enterprise customers now an important growth driver.
- Brannin McBee said the company’s main bottleneck is now powered shells, transformers, batteries, and skilled electricians rather than just GPU supply.
- Brannin McBee said AI labs are extending commitments from three years to five years and asking for larger, uninterrupted deployments.
- Brannin McBee said inference already represents well in excess of 50% of infrastructure utilization on CoreWeave’s platform.
- Brannin McBee argued that GPU compute is not fungible enough yet to support a liquid commodity market.
Notable quotes
“we're not seeing any pullback on on what they're doing on on inference today”
“I think that that is unsustainable. But do we see adoption in other sectors and how this can continue to spread out? Absolutely”
“our financial services client backlog is in the tens of billions of dollars”
“Having a powered shell is the bottleneck. Okay. today”
“it's not getting easier to to build operate provision deliver these GPUs it's getting more difficult”
How the episode opens
Bloomberg Audio Studios podcasts, radio, news. — Hello and welcome to another episode of the OddLots podcast. I'm Joe Weisenthal — And I'm Tracy Aloway. Tracy, I'm envisioning this future
Where like we have to do a uh a state of the sort of AI inference market episode like once a month, you know, like where it's like things are moving so rapidly and there's so much change either in terms of what models are using or what they're being used for, etc. that in the same way we would do like you know the occasional regular stock market episode or whatever we would just do okay what are we seeing right now in AI inference trends because it just feels like the moment we do an episode a few weeks later it may be out of date
We should just bite the bullet and do a weekly episode transform lots more into a market update on compute — We could do inference inf uh I don't know we'll have to workshop this — Inference no — No we'd have to um but anyway this is lots inference.
Lots of inference. This is like the story of the moment and we know that you know a couple years ago everyone was sort of dabbling around with various things and experimenting and using AI like oh like write a poem for me about this etc. That phase of AI is long over and we know that companies specifically are spending a ton on compute.
So much so that CFOs around the world are getting sticker shock about their compute budgets. And there was even a headline of like Uber saying like, okay, like $1,500 of max per employee, like don't spend more than that in a month on tokens.
From the episode’s captions: roughly the first two minutes, lightly cleaned. Keep watching on YouTube →
Topics
- compute market
- gpu supply constraints
- electricity bottlenecks
- training versus inference
- standardizing compute
Companies and tickers mentioned
- NVDA
- CoreWeave
- Nvidia
Watch the episode
Watch “How CoreWeave Sees the Market for Compute Right Now | Odd Lots” on YouTube
Summary, takeaways and quote selection by Octagon. Quotes are short excerpts; the full conversation is in the episode.
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