Jane Street signs $6 billion AI cloud deal with CoreWeave, invests $1 billion in equity


In short: Jane Street has signed a $6 billion AI cloud agreement with CoreWeave and taken a $1 billion equity stake at $109 per share, making the quantitative trading firm one of CoreWeave’s five largest shareholders. The deal provides Jane Street with access to NVIDIA’s next-generation Vera Rubin compute and adds to CoreWeave’s growing contract book, which includes Meta ($35B), OpenAI ($12B), and NVIDIA ($6.3B in capacity commitments).

Jane Street, the quantitative trading firm that generated $20.5 billion in net trading revenue last year, has signed a $6 billion AI cloud agreement with CoreWeave and taken a $1 billion equity stake in the company, a deal that says as much about the future of finance as it does about the AI infrastructure market.

Under the agreement, CoreWeave will provide Jane Street with access to next-generation compute across multiple data centre facilities, including systems built on NVIDIA’s forthcoming Vera Rubin architecture. Jane Street’s $1 billion equity investment, at $109 per share, makes it one of CoreWeave’s five largest shareholders and values the cloud provider’s stock at a 176% premium to its IPO price just thirteen months ago.

Why a trading firm needs $6 billion in cloud compute

Jane Street is not a typical CoreWeave customer. The firm, founded in 2000 with offices in New York, London, Hong Kong, Singapore, and Amsterdam, runs a research-driven trading operation that already deploys tens of thousands of high-end GPUs across its own computing infrastructure. Its engineers build neural network models that power trading strategies across global financial markets, processing massive volumes of noisy market data in real time.

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The firm’s statement framed the deal in language usually reserved for AI research labs: “training large, complex models on massive volumes of noisy data, refining them continuously, and deploying at a scale to help make markets more efficient.” Max Hjelm, CoreWeave’s senior vice president of revenue, was more direct: “Jane Street operates like a frontier lab.

That comparison is not hyperbole. Jane Street’s 2024 net income was $13 billion, roughly what it costs to train a frontier language model several times over. Through the first three quarters of 2025, the firm’s revenue had already exceeded $24 billion, with a single quarter, Q2 2025, producing $10.1 billion in net trading revenue. This is a company with both the appetite and the capital to consume compute at frontier scale.

CoreWeave’s contract machine

For CoreWeave, the deal extends a pattern that has transformed it from a niche GPU cloud provider into one of the most consequential infrastructure companies in AI. The company went public on Nasdaq in March 2025 at $40 per share, raising $1.5 billion at a valuation of roughly $23 billion. Since then, it has signed contracts that dwarf its own market capitalisation at IPO.

Meta’s deal alone is worth $35 billion through 2032, expanded from an initial commitment in an agreement announced earlier this month. OpenAI has committed approximately $12 billion over five years. NVIDIA itself invested $2 billion in CoreWeave in January 2026 and separately agreed to purchase $6.3 billion in unsold compute capacity through April 2032, effectively underwriting CoreWeave’s buildout with a demand guarantee. Jane Street’s $6 billion commitment adds another major customer to a roster that also includes Anthropic, Google, and Microsoft.

The concentration of AI spending among a handful of cloud providers is reshaping the infrastructure market. CoreWeave’s pitch is specialisation: rather than competing with AWS or Azure across the full spectrum of cloud services, it builds exclusively for AI workloads, offering dedicated connectivity, custom storage configurations, and the kind of responsive technical support that general-purpose cloud providers struggle to match for demanding customers.

The Vera Rubin factor

The agreement specifies access to NVIDIA’s Vera Rubin technology, the next-generation GPU platform that NVIDIA claims will deliver up to ten times lower cost per token compared to its current Blackwell architecture. CoreWeave is among the first cloud providers to offer Vera Rubin systems, with deployment beginning in Q2 2026.

For Jane Street, the appeal is clear. Quantitative trading models are becoming deeper and more computationally expensive, and the firms that can train and refine them fastest have a direct competitive advantage. Access to next-generation silicon before competitors do is not a nice-to-have; in a business where nanoseconds matter, it is the difference between capturing and missing a trade.

The equity investment reinforces the point. By taking a $1 billion stake in CoreWeave, Jane Street is not just buying cloud capacity; it is aligning its financial interests with the continued buildout of the infrastructure it depends on. If CoreWeave succeeds, Jane Street benefits both as a customer and as a shareholder.

What this signals

The deal is the latest evidence that the boundary between AI companies and their customers is dissolving. Jane Street is a trading firm, but it operates its own GPU clusters, employs machine learning researchers, and now invests directly in AI infrastructure providers. The same pattern is visible across finance: hedge funds, high-frequency trading firms, and quantitative asset managers are all committing billions to the compute infrastructure that powers their models.

This has implications beyond Wall Street. CoreWeave’s ability to sign contracts totalling tens of billions of dollars rests on the assumption that demand for AI compute will continue to grow at rates that justify massive capital expenditure. The company’s customers are, in effect, pre-funding a buildout that will take years to complete. If AI compute demand plateaus or shifts to more efficient architectures faster than expected, the long-term contracts that underpin CoreWeave’s valuation become liabilities rather than assets.

For now, the demand signal is unambiguous. Between Meta, OpenAI, NVIDIA, Jane Street, and a growing list of enterprise customers, CoreWeave has secured commitments that would have been difficult to imagine when it listed thirteen months ago. The company’s stock has nearly tripled since its IPO, and each new contract reinforces the thesis that specialised AI cloud providers can compete with, and in some cases outperform, the hyperscalers on workloads that matter most.

Jane Street’s bet is that the returns on AI-driven trading will justify $6 billion in cloud spending and a $1 billion equity position in the company providing it. Given that the firm made $13 billion in net income last year, the maths is not hard to see. The harder question is whether the broader AI infrastructure boom, in which a handful of companies are committing capital at a pace not seen since the fibre-optic buildout of the late 1990s, will produce returns to match. Jane Street, at least, is trading as though it will.



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Recent Reviews


As I’m writing this, NVIDIA is the largest company in the world, with a market cap exceeding $4 trillion. Team Green is now the leader among the Magnificent Seven of the tech world, having surpassed them all in just a few short years.

The company has managed to reach these incredible heights with smart planning and by making the right moves for decades, the latest being the decision to sell shovels during the AI gold rush. Considering the current hardware landscape, there’s simply no reason for NVIDIA to rush a new gaming GPU generation for at least a few years. Here’s why.

Scarcity has become the new normal

Not even Nvidia is powerful enough to overcome market constraints

Global memory shortages have been a reality since late 2025, and they aren’t just affecting RAM and storage manufacturers. Rather, this impacts every company making any product that contains memory or storage—including graphics cards.

Since NVIDIA sells GPU and memory bundles to its partners, which they then solder onto PCBs and add cooling to create full-blown graphics cards, this means that NVIDIA doesn’t just have to battle other tech giants to secure a chunk of TSMC’s limited production capacity to produce its GPU chips. It also has to procure massive amounts of GPU memory, which has never been harder or more expensive to obtain.

While a company as large as NVIDIA certainly has long-term contracts that guarantee stable memory prices, those contracts aren’t going to last forever. The company has likely had to sign new ones, considering the GPU price surge that began at the beginning of 2026, with gaming graphics cards still being overpriced.

With GPU memory costing more than ever, NVIDIA has little reason to rush a new gaming GPU generation, because its gaming earnings are just a drop in the bucket compared to its total earnings.

NVIDIA is an AI company now

Gaming GPUs are taking a back seat

A graph showing NVIDIA revenue breakdown in the last few years. Credit: appeconomyinsights.com

NVIDIA’s gaming division had been its golden goose for decades, but come 2022, the company’s data center and AI division’s revenue started to balloon dramatically. By the beginning of fiscal year 2023, data center and AI revenue had surpassed that of the gaming division.

In fiscal year 2026 (which began on July 1, 2025, and ends on June 30, 2026), NVIDIA’s gaming revenue has contributed less than 8% of the company’s total earnings so far. On the other hand, the data center division has made almost 90% of NVIDIA’s total revenue in fiscal year 2026. What I’m trying to say is that NVIDIA is no longer a gaming company—it’s all about AI now.

Considering that we’re in the middle of the biggest memory shortage in history, and that its AI GPUs rake in almost ten times the revenue of gaming GPUs, there’s little reason for NVIDIA to funnel exorbitantly priced memory toward gaming GPUs. It’s much more profitable to put every memory chip they can get their hands on into AI GPU racks and continue receiving mountains of cash by selling them to AI behemoths.

The RTX 50 Super GPUs might never get released

A sign of times to come

NVIDIA’s RTX 50 Super series was supposed to increase memory capacity of its most popular gaming GPUs. The 16GB RTX 5080 was to be superseded by a 24GB RTX 5080 Super; the same fate would await the 16GB RTX 5070 Ti, while the 18GB RTX 5070 Super was to replace its 12GB non-Super sibling. But according to recent reports, NVIDIA has put it on ice.

The RTX 50 Super launch had been slated for this year’s CES in January, but after missing the show, it now looks like NVIDIA has delayed the lineup indefinitely. According to a recent report, NVIDIA doesn’t plan to launch a single new gaming GPU in 2026. Worse still, the RTX 60 series, which had been expected to debut sometime in 2027, has also been delayed.

A report by The Information (via Tom’s Hardware) states that NVIDIA had finalized the design and specs of its RTX 50 Super refresh, but the RAM-pocalypse threw a wrench into the works, forcing the company to “deprioritize RTX 50 Super production.” In other words, it’s exactly what I said a few paragraphs ago: selling enterprise GPU racks to AI companies is far more lucrative than selling comparatively cheaper GPUs to gamers, especially now that memory prices have been skyrocketing.

Before putting the RTX 50 series on ice, NVIDIA had already slashed its gaming GPU supply by about a fifth and started prioritizing models with less VRAM, like the 8GB versions of the RTX 5060 and RTX 5060 Ti, so this news isn’t that surprising.

So when can we expect RTX 60 GPUs?

Late 2028-ish?

A GPU with a pile of money around it. Credit: Lucas Gouveia / How-To Geek

The good news is that the RTX 60 series is definitely in the pipeline, and we will see it sooner or later. The bad news is that its release date is up in the air, and it’s best not to even think about pricing. The word on the street around CES 2026 was that NVIDIA would release the RTX 60 series in mid-2027, give or take a few months. But as of this writing, it’s increasingly likely we won’t see RTX 60 GPUs until 2028.

If you’ve been following the discussion around memory shortages, this won’t be surprising. In late 2025, the prognosis was that we wouldn’t see the end of the RAM-pocalypse until 2027, maybe 2028. But a recent statement by SK Hynix chairman (the company is one of the world’s three largest memory manufacturers) warns that the global memory shortage may last well into 2030.

If that turns out to be true, and if the global AI data center boom doesn’t slow down in the next few years, I wouldn’t be surprised if NVIDIA delays the RTX 60 GPUs as long as possible. There’s a good chance we won’t see them until the second half of 2028, and I wouldn’t be surprised if they miss that window as well if memory supply doesn’t recover by then. Data center GPUs are simply too profitable for NVIDIA to reserve a meaningful portion of memory for gaming graphics cards as long as shortages persist.


At least current-gen gaming GPUs are still a great option for any PC gamer

If there is a silver lining here, it is that current-gen gaming GPUs (NVIDIA RTX 50 and AMD Radeon RX 90) are still more than powerful enough for any current AAA title. Considering that Sony is reportedly delaying the PlayStation 6 and that global PC shipments are projected to see a sharp, double-digit decline in 2026, game developers have little incentive to push requirements beyond what current hardware can handle.

DLSS 5, on the other hand, may be the future of gaming, but no one likes it, and it will take a few years (and likely the arrival of the RTX 60 lineup) for it to mature and become usable on anything that’s not a heckin’ RTX 5090.

If you’re open to buying used GPUs, even last-gen gaming graphics cards offer tons of performance and are able to rein in any AAA game you throw at them. While we likely won’t get a new gaming GPU from NVIDIA for at least a few years, at least the ones we’ve got are great today and will continue to chew through any game for the foreseeable future.



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