Neocloud: The Infrastructure Shift You Might Be Missing
And other useful things
I just learned about Neocloud from my friend Yvette (if you don’t know her, then you’re missing out on TWO awesome topics).
If you already knew about it, congratulations. You can stop reading, now.
If you didn’t, you’re in good company. But this behind‑the‑scenes shift in how AI gets built and deployed deserves a seat at the table, especially if you work with model training, data science, or infrastructure strategy.
What Neocloud Actually Is
Neocloud refers to a new class of GPU-focused cloud providers built specifically for AI workloads. These are not general-purpose platforms. They do not compete on breadth. They exist to give developers and researchers access to high-end GPU clusters fast, with less overhead and at a lower cost than the big three cloud providers.
Companies like CoreWeave, Voltage Park, Crusoe, Lambda Labs, and Nebius are offering pay-per-GPU-hour infrastructure. No bundled services. No layers of abstraction. Just the compute you need for training, tuning, or running models.
Why This Exists
In early 2024, demand for GPUs, especially NVIDIA H100s, surged past supply. Hyperscalers were booked, expensive, and slow. You couldn’t spin up a multi-node training cluster on demand anymore. The bottleneck created space for smaller providers to meet that demand. Their business model is simple. They buy hardware, host it, and make it easy to rent.
This is not about trying to replace AWS. It's about offering something AWS cannot: speed, predictability, and affordability for specialized workloads.
What Makes These Clouds Different
Most cloud platforms offer hundreds of services. Neocloud providers offer one: access to high-performance GPUs.
They keep pricing flat and transparent. Provisioning is often immediate. Networking is tuned for AI workloads. And you often get bare metal access, which means no virtualization layers slowing you down.
Some advantages:
Predictable cost per GPU hour
Instant or near-instant provisioning
Optimized bandwidth for multi-GPU tasks
Access to newer hardware sooner
No unnecessary services inflating your bill
Companies Worth Knowing
CoreWeave recently went public and has landed deals with OpenAI and Google. They’re a major player with access to high volumes of GPUs.
Voltage Park is run by a nonprofit linked to Jed McCaleb. They offer full clusters and emphasize transparent pricing. Their customer base includes research labs and emerging AI companies.
Crusoe Cloud is doing something different. They run data centers using flare gas—essentially turning waste energy into compute infrastructure. It’s an environmentally conscious approach to AI infrastructure.
Lambda Labs has carved out a space serving startups, independent developers, and researchers. They are known for good documentation and developer-friendly tools.
Nebius is a spinout from Yandex’s AI division. They raised more than 700 million dollars to build out sovereign and enterprise infrastructure in the US and Europe.
Why It Matters for You
If you’re building, training, or running large models, these services offer an alternative to AWS or Azure. You may still use the big clouds for storage or orchestration, but when you need to train a model in weeks, not quarters, this is how you get it done.
You can prototype without asking for procurement approvals. You can control costs with fewer surprises. And if you are already stretching your infrastructure team thin, this is a way to speed up delivery without hiring more staff.
Neocloud lets you focus on product velocity without tying you to long-term contracts or managed services you don’t need.
What Comes Next
Nvidia knows this shift is happening. They launched Lepton, a service that connects developers to multiple GPU cloud providers. That’s not about convenience. That’s about scaling AI infrastructure in a fragmented market. Even the hardware vendors are building around the idea that AI workloads need a different kind of cloud.
If you’re a product leader, a researcher, or anyone trying to make sense of your infrastructure roadmap, Neocloud is not a theory. It’s already part of the architecture behind many of the tools you’re using. Understanding it now puts you ahead of the people who are still treating AWS as the only option.
If you’re experimenting with any of these platforms, I’d like to hear about it. If you’re not, this might be the time to start.
Sources
CoreWeave.com
VoltagePark.com
CrusoeCloud.com
LambdaLabs.com
Nebius.ai
RCR Wireless News
Uptime Institute
PR Newswire
Financial Times
SemiAnalysis
NextDC
The Wall Street Journal
Wikipedia
Reddit r/MachineLearning and r/LocalLLaMA