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The Next Platform: In-depth coverage of high end computing

Uncle Sam Awards $2 Billion-Plus To Quantum Companies, But Wants A Cut Oak Ridge Starts Weaving Together A Quantum, Classical HPC, And AI System Stack Dell Bulks Up Hardware As AI Infrastructure Shifts To On-Premises Cisco Wins Over AI Customers With Merchant Silicon And Optics With Its IPO Done, Cerebras Can Get Back To Pushing The AI Envelope HPE Throws VM Users A Lifeline, Unifying Containers And VM Management In Cloud Stack OpenAI, Microsoft And Friends Build A Better, More Scalable Ethernet Compute And Memory Price Hikes Drive IT Spending Way Higher Sometimes, Air Is The Only Way For AI Systems To Keep Their Cool Arista Rides AI Scale Out Networks, Moves Into Scale Across, And Awaits Scale Up If You Can Make A Compute Engine, You Can Sell A Compute Engine Cleveland Clinic Simulates Large Proteins With Quantum-Centric Supercomputing Broadcom Helps CPU And XPU Makers Go Vertical With Compute Microsoft Committed To Doubling AI Infrastructure In Two Years Google Is A Full Stack AI Player, And Is Playing Well AWS Will Be An OEM, Just Like Google And Maybe Microsoft New Google Networks Tuned Up For GenAI Inference And Training Microsoft And OpenAI Remain Friends, Are Looking To Hook Up With Others AI-Driven CPU Shortage Saves Intel’s Financial Cookies The GenAI Battle Shifts From Frontier Models To Agentic Platforms With TPU 8, Google Makes GenAI Systems Much Better, Not Just Bigger Cisco Scales Out Quantum Systems With A Quantum Network Switch The Second Time Will Be The IPO Charm For Cerebras Imagine An Army Of AI Minions Handling Incident Response AI Will Soon Drive A Third Of TSMC’s Business Bechtolsheim & Friends Breathe Life Into Pluggable Optics One Last Time How HPC And AI Digital Twins Accelerate Quantum Error Correction The Embrace Of AI In Design Transforms Cadence And Its Customers Nvidia Brings The Power Of Open Source AI Models To Quantum Computing Building The Imperfect Beast For Enterprises, GPUs Need Virtualization As Much As CPUs Ever Did Contemplating Meta’s Homegrown MTIA Compute Engine Roadmap Most Neoclouds, Sovereigns, And Enterprises Will Buy, Not Build, Their AI Stacks Broadcom And Google Benefit Mightily From Anthropic’s Meteoric Growth Rebellions AI Rings Up The Money To Rack Up AI Inference Systems Nvidia Software Pushes MLPerf Inference Benchmarks To New Highs Broadcom Makes Its Pitch To Run Kubernetes On VMware VCF The $2 Billion Nvidia Deal With Marvell Is About A Lot More Than NVLink Fusion Classiq Says Quantum Is On Its Way, But Patience Is Needed Demonstrating The Scientific Usefulness Of Quantum Systems We Need Servers – Lots Of Servers. . . . Arm Comes Full Circle With Homegrown, AI-Tuned Server CPU Riding The Memory Boom And Trying To Avoid The Bust Data Analytics Helps Make The Mighty Lionesses Roar Driving Down The AI System Roadmap With Nvidia The Open Agentic AI World According To Nvidia Nvidia Finally Admits Why It Shelled Out $20 Billion For Groq Nvidia Says OpenClaw Is To Agentic AI What GPT Was To Chattybots IBM Unrolls Blueprint For Quantum-Classical HPC Computing Women Get Data-Driven Health Boost As The FA Tackles Sports Science Four Months Into Its Comeback, Zapata Stakes Its Claim In Quantum Software Eridu Cuts To The AI Networking Chase With High Radix Switch System HPE Works Harder And Smarter To Chase Datacenter Profits We Need A Proper AI Inference Benchmark Test How AI Is Boosting Gender Equality In High Performance Racing Custom Compute Engine Biz Growing More Than Marvell Ever Hoped Broadcom May Become The Biggest Counterbalance To Nvidia Ayar Labs Gets $500 Million To Ramp Photonics Into 2028 AI Systems With Cisco Outshift, Agentic AI Is Teed Up For the Internet Of Cognition Nvidia Sees The Light On Silicon Photonics And Maybe Optical Switching AI Servers Finally Dominate Dell’s Systems Business VAST Data: What Controls The Data Is More Important Than What Stores It So Far, Nobody Turns Tokens Into Money Like Nvidia SambaNova Pits Its Engineering Against Nvidia For Agentic AI Some More Game Theory, This Time On The AMD-Meta Platforms Deal AMD Says “Helios” Racks And MI400 Series GPUs On Track For 2H 2026 CPU-Only Compute Still Matters To A Lot Of HPC Centers Taalas Etches AI Models Onto Transistors To Rocket Boost Inference Some Game Theory On That Nvidia-Meta Platforms Partnership AI Eats The World, And Most Of Its Flash Storage The Current AI Networking Wave Will Be A Tsunami Of Money By 2027 The Memory Crunch Pinches Cisco’s Profits Only A Few AI Platforms Can Survive The Greatest AI Show On Earth Cisco Doubles Up The Switch Bandwidth To Take On AI Scale Out And Eventually Scale Up Datacenter Spending Forecast Revised Upwards – Yet Again The Twin Engine Strategy That Propels AWS Is Working Well With GenAI Turbochargers, Google Is Shifting Its Cloud Into A Higher Gear AMD Finally Makes More Money On GPUs Than CPUs In A Quarter Dassault And Nvidia Bring Industrial World Models To Physical AI TACC Explores Mixed Precision And FP64 Emulation For HPC With Horizon Robotics Will Break AI infrastructure: Here's What Comes Next Oracle’s Financing Primes The OpenAI Pump Gartner Takes Another Stab At Forecasting AI Spending Microsoft Is More Dependent On OpenAI Than The Converse Big Blue Poised To Peddle Lots Of On Premises GenAI Microsoft Takes On Other Clouds With “Braga” Maia 200 AI Compute Engines Nvidia’s $2 Billion Investment In CoreWeave Is A Drop In A $250 Billion Bucket Intel Is Still Struggling In The Datacenter, But It Could Get Better Is Nvidia Assembling The Parts For Its Next Inference Platform? TSMC Has No Choice But To Trust The Sunny AI Forecasts Of Its Customers Cerebras Inks Transformative $10 Billion Inference Deal With OpenAI By Decade’s End, AI Will Drive More Than Half Of All Chip Sales Startup Quantum Elements Brings AI, Digital Twins To Quantum Computing D-Wave Makes Gate-Model Power Move With Quantum Circuits Buy Building The Future Of Software In The AI-Native Era Arista Modular Switches Aim At Scale Across Networks, Hit Scale Out, Too NextSilicon Takes Aim At CPUs And GPUs With “Maverick-2” Dataflow Engine How HPC Is Igniting Discoveries In Dinosaur Locomotion – And Beyond Oracle First In Line For AMD “Altair” MI450 GPUs, “Helios” Racks
CoreWeave Takes As Much Financial Engineering As It Does Datacenter Design
Timothy Prickett Morgan · 2026-04-10 · via The Next Platform: In-depth coverage of high end computing

Meta Platforms has aspirations to be one of the big AI model builders and to push the state of the art to “superintelligence,” under the impression that it can sell access to personal AI agents to its more than 1 billion users worldwide. It is a reasonable business model – and a lot more sensible than the metaverse that was the obsession of company founder Mark Zuckerberg a few years and a few tens of billions of dollars ago.

While the social network and AI model maker has a fondness for its own server, storage, switch, and datacenter designs, even after the launch of the Open Compute Project and its open strategy firmly charted, the company has not been shy about renting datacenter capacity when and where it needed to. And in the GenAI boom, Meta Platforms has not shied away from renting compute capacity from others.

Back in September 2025, Meta Platforms inked a supplier deal with king of the neoclouds, CoreWeave, that saw the former buy $14.2 billion in AI processing capacity through December 2031. This was a big deal for CoreWeave, which had just gone public and which needed to show that it has customers other than Microsoft renting its GPU hours. With the deal announced today in an 8-K filing with the US Securities and Exchange Commission, CoreWeave said that Meta Platforms has signed up for an additional $21 billion in AI processing capacity running out through December 2032.

No one knows the ramp of that capacity usage, and it is no doubt nailed down pretty hard because the one thing CoreWeave can’t have is a GPU burning capital and electricity and a customer not paying for the privilege of using it. It is not safe to assume that all $21 billion of spending happens in 2032, the incremental year, but for all we know that is exactly what will happen.

This deal will bring CoreWeave’s revenue backlog up to $87.8 billion, and Meta Platforms will represent 40.1 percent of that backlog. Back in March 2025, OpenAI inked a five year deal with CoreWeave for $11.9 billion in capacity, and another $10.5 billion in capacity was added last year, bringing the total to $22.4 billion in capacity. Assuming that none of that OpenAI capacity has been activated as yet, that would represent 25.5 percent of that extended backlog. So these two customers – Meta Platforms and OpenAI – represent nearly two-thirds of the guaranteed revenue on the books. In 2024, Microsoft represented 62 percent of the company’s $1.92 billion in sales, and CoreWeave’s top three customers accounted for 77 percent of revenues.

CoreWeave only has two dozen named customers as far as we can tell, and no doubt will have more, especially as its big clients roll off old iron and onto new stuff. In fact, that is the whole neocloud business model. Keep the GPUs humming for seven or eight years and sell the old capacity to enterprises, governments, startups, and others as the tech titans pay to rent the new GPU systems as they come hot out of the factories.

In all of 2025, CoreWeave had $5.13 billion in sales, up 2.7X from 2024, and it had an operating loss of $46 million, but due to stock compensation and other factors, it posted a net loss of $1.17 billion.  The losses are at least growing slower than the revenue, unlike some fast-growing startups.

The company has just shy of $4 billion in cash and marketable securities, which is partly due to going public last March. Thanks to hefty outside investment, however, CoreWeave was able to spend $14.9 billion on capital equipment expenses, building out its datacenter fleet to 43 centers. It ended 2025 with 850 megawatts of active power – we think CoreWeave has maybe 600,000 GPUs, mostly Nvidia “Hopper” H100s and H200s with a rising number of “Blackwell” B200s and B300s. The company has 3.5 megawatts of total power under contract, which is a measure of how big it can build itself without having to scrounge for more juice. By the way, assuming there has not been much in the way of depreciation on those GPUs, they are worth somewhere between $15 billion and $20 billion. That's a fair amount of collatoral.

It is going to take more money than CoreWeave wants to tap from its balance sheet to start building out that 2.25 gigawatts of unused contracted power – at the $50 billion per gigawatts figure that Nvidia co-founder and chief executive officer Jensen Huang cites, and assuming that CoreWeave continues to be an Nvidia-only shop (a fair assumption), we are talking about CoreWeave needing on the order of $113 billion to build out that unused capacity, which might rent for 4X to 5X that amount on a one of the big cloud builders over a bunch of years and maybe half that on a neocloud, which exists to be cheaper and focused on AI.

To help cover its datacenter expansion costs, CoreWeave said this morning that it was doing a private offering of $1.25 billion in senior notes that would come due in 2031, and by the afternoon, that amount was raised to $1.75 billion in notes. The company also said that it was going to offer $3 billion in senior notes that could be convertible to its stock. These notes would come due in 2031 as well.

Back in February, CoreWeave said that it would spend somewhere between $6 billion and $7 billion on capital expenses, and for the full 2026 year expected to invest somewhere between $30 billion and $35 billion. That’s a tall order for a company with just under $4 billion in the bank, but CoreWeave has some very rich friends – think the green eye of Horus – who want there to be alternatives to Amazon Web Services, Microsoft Azure, and Google Cloud, all of whom buy lots of GPUs from Nvidia but who also spend a lot of time designing and deploying their own custom AI accelerators.