We’re in the middle of an AI gold rush. While tons of companies are building the next cool app, there’s another group of companies quietly providing the "picks and shovels", the essential infrastructure that makes this whole AI revolution possible.
One of the biggest, though maybe less visible, players here is CoreWeave. They supply the raw computing power that helps some of the biggest names in tech, like OpenAI and Meta, build their AI models.
In this article, we’ll give you a straightforward look at what CoreWeave does, who it’s for, and what it costs. We’ll also clear up the difference between foundational AI infrastructure like CoreWeave and practical AI applications that any business can start using to solve real problems right now.
What is CoreWeave?
At its core, CoreWeave is a specialized cloud provider built for one thing: handling massive computing jobs. In simple terms, they offer the super-powered environment needed to train and run the large-scale AI models you hear about all the time.
What makes them different from general cloud providers like Amazon Web Services (AWS) or Google Cloud is their laser focus. Instead of trying to do a bit of everything, CoreWeave concentrates on offering a huge supply of the latest and greatest NVIDIA GPUs (Graphics Processing Units). They’ve optimized everything for performance, offering a scale that’s hard to find elsewhere.
Founded back in 2017, the company has become a go-to partner for AI labs and big companies, especially as the demand for top-tier GPUs has gone through the roof. If you think of the entire AI technology stack, CoreWeave provides the very bottom layer, the compute power. It’s like the engine room of a massive ship, not the shiny vessel itself. Most businesses will end up using an AI application that’s built on top of this kind of powerful infrastructure.
CoreWeave’s services: The building blocks of AI
CoreWeave’s offerings are basically the raw ingredients you’d need if you wanted to build a sophisticated AI model from the ground up. It’s a powerful set of tools, but you need the expertise and resources to actually use them.
GPU and CPU compute
Their main service is renting out access to incredibly powerful hardware. We’re talking top-of-the-line NVIDIA GPUs like the H100 and A100. GPUs are the workhorses of AI because they can perform thousands of calculations at once (a thing called parallel processing), which is exactly what you need to train complex AI models on enormous amounts of data.
Specialized storage and networking
Training a huge AI model isn’t just about raw power; it’s also about data, and moving that data around really, really fast. CoreWeave provides high-speed storage and networking built to avoid traffic jams, making sure those expensive GPUs aren’t just sitting around waiting for data to arrive.
Managed platform services
To help tame all this complexity, CoreWeave offers a platform built on Kubernetes, which is the industry standard for managing large-scale applications. This helps development teams get their AI workloads running and scaled up without having to micromanage every single piece of the hardware underneath.
While this setup is amazing for building AI from scratch, most businesses don’t need to get this deep into the weeds. Usually, the goal is to fix a business problem, like improving customer support, not managing a cluster of servers. This is where AI applications like eesel AI fit in. They deliver the benefits of AI by simply integrating with the tools your team already uses.
Who uses CoreWeave?
CoreWeave’s client list is pretty much a who’s who of the current AI scene, which tells you a lot about the scale they operate at.
They work with the teams building the huge, foundational models that many other companies then build upon.
A couple of standout customers and deals:
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OpenAI: As one of their first major clients, OpenAI has leaned heavily on CoreWeave’s infrastructure. In a testimonial, CEO Sam Altman referred to CoreWeave as one of their "earliest and largest compute partners," which shows just how important they were in building the models OpenAI is famous for.
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Meta: The social media giant recently inked a massive $14.2 billion deal with CoreWeave. This long-term agreement is a key part of Meta’s plan to expand its AI capabilities, from its Llama models to new AI features across its apps.
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Mistral AI: This innovative French AI lab uses CoreWeave’s clusters to speed up the training of their popular open-source models, which helps them keep pace with much larger competitors.
So what are they doing with all that power?
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Large Language Model (LLM) Training: This is the big one. It often requires thousands of GPUs running around the clock for weeks or months just to create one new foundational model.
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AI Inference: After a model is trained, you need a place to run it so it can answer user questions. That’s called inference, and it also takes a lot of GPU power, especially when you have millions of users.
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Other heavy-duty tasks: Their infrastructure is also used for things like high-end visual effects (VFX) rendering for movies and complex scientific simulations.
These billion-dollar deals show just how much money it takes to build AI from the ground up. The good news? Your business can get all the benefits of AI without needing a venture capital-sized budget. With a platform like eesel AI, you can deploy a smart AI agent that learns from your existing helpdesk tickets and knowledge sources like Confluence or Google Docs in just a few minutes, giving you immediate value.
How CoreWeave’s business model and pricing work
To get a real sense of who CoreWeave is for, you have to look at how they charge for their services.
A look at pricing
CoreWeave uses a pay-as-you-go model. Customers are billed by the hour for the hardware they use. This is flexible for teams that need to ramp resources up and down, but it can also lead to some eye-watering bills if you’re not careful. A single training job that runs for a long time can easily cost tens of thousands of dollars.
Here’s a quick look at their on-demand pricing for a few popular GPU options:
| GPU Instance | GPUs | VRAM (per GPU) | vCPUs | System RAM (GB) | Price (Per Hour) |
|---|---|---|---|---|---|
| NVIDIA HGX H100 | 8 | 80 GB | 128 | 2,048 | $49.24 |
| NVIDIA A100 | 8 | 80 GB | 128 | 2,048 | $21.60 |
| NVIDIA L40S | 8 | 48 GB | 128 | 1,024 | $18.00 |
A heads-up: These prices are just for illustration. For the latest numbers, you should always check the official CoreWeave pricing page.
On top of the raw compute costs, you also have to pay for storage and moving data around, which makes estimating the final bill even trickier.
This hardware-focused pricing is great for teams that want total control, but it’s not a simple, all-inclusive package. In contrast, platforms like eesel AI offer clear, predictable plans based on how much your AI is used. You know exactly what you’ll pay each month, making it much easier to budget and show a return on your investment, with no surprise compute fees.
This video discusses CoreWeave's position in the market as a specialized AI infrastructure provider.
Market position and risks
As a publicly traded company (ticker: CRWV), CoreWeave is a big deal in the AI infrastructure world. But as some financial analysts have noted, their business model has an interesting risk. Their biggest customers, like Microsoft (a huge partner of OpenAI) and Meta, are also their biggest potential competitors.
These tech giants are pouring billions into building their own custom data centers. The long-term question is whether they’ll eventually rely less on third-party providers like CoreWeave once their own infrastructure is fully up and running. It makes CoreWeave a really interesting, high-stakes company to watch.
The takeaway: Do you need CoreWeave or an AI application?
After all that, how do you know which path is right for you? It really just depends on what you’re trying to do.
You probably need a service like CoreWeave if:
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You’re a large company or a well-funded AI startup with serious technical chops.
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You have a full-time team of machine learning engineers and data scientists.
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Your main goal is to build a brand new, custom AI model from scratch.
You probably need an AI application like eesel AI if:
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You want to use proven AI to solve a specific business problem, like automating customer support or giving instant answers to your internal teams.
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You need something that works with the tools you already have, like Zendesk, Slack, or Jira Service Management, right away.
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You want to get up and running in minutes, not months, without needing a team of developers to do it.
The right tool for the job
CoreWeave is a hugely important part of the AI ecosystem. They are the ones building the engines, providing the raw power that lets researchers create incredible new models. Without companies like them, the pace of innovation would be a lot slower.
But for most businesses, the real opportunity isn’t in building the engine, it’s in driving the car. The immediate value comes from using ready-made AI applications that solve real problems, make your team more efficient, and keep your customers happy.
Ready to put AI to work for your support team, without the headache of managing infrastructure? eesel AI connects to your helpdesk and knowledge bases to automate answers and help your agents in an instant. Give it a try with a free trial today.
Frequently asked questions
CoreWeave is a specialized cloud provider focused intensely on high-performance computing, particularly for AI workloads. Unlike general providers such as AWS or Google Cloud, CoreWeave optimizes its entire infrastructure for NVIDIA GPUs to offer unparalleled scale and speed for tasks like large language model training.
CoreWeave primarily serves large companies, well-funded AI startups, and research labs that are building foundational AI models from scratch. Their client list includes major players like OpenAI and Meta, who require massive GPU clusters for LLM training and inference.
Generally, CoreWeave is not designed for small or medium-sized businesses unless they possess deep technical expertise and a specific need to build AI models from the ground up. Most SMBs will find more immediate and practical value in ready-made AI applications that solve specific business problems.
CoreWeave uses a pay-as-you-go model, billing customers hourly for the hardware they use, including powerful NVIDIA GPUs. Additional costs apply for specialized storage and high-speed networking, making the overall expense tied directly to resource consumption.
CoreWeave’s main offerings include access to top-tier NVIDIA GPUs (like H100s and A100s) for high-performance compute. They also provide specialized high-speed storage, optimized networking, and managed platform services built on Kubernetes to help clients manage complex AI workloads.
A notable risk for CoreWeave is that some of its largest customers, like Microsoft and Meta, are also heavily investing in building their own custom data centers. This could lead to reduced reliance on third-party providers in the long term, posing a competitive challenge.
Companies should choose CoreWeave if they have a dedicated team of ML engineers to build custom AI models from scratch, requiring raw GPU power and infrastructure control. Conversely, a ready-made AI application is better for businesses seeking to quickly deploy AI to solve specific problems using existing tools, without managing complex infrastructure.
