Training or serving large AI models needs GPUs, and renting them from a hyperscaler like AWS or Google Cloud isn't the only option anymore — a wave of GPU-specialist clouds has built businesses entirely around NVIDIA hardware, often at better prices and with faster provisioning. Two of the bigger names in that wave are CoreWeave, the enterprise-scale incumbent already running workloads for major AI labs, and Nebius, a publicly-traded European challenger positioning itself as a transparent alternative to both CoreWeave and the US hyperscalers. Here's what actually separates them.
CoreWeave
CoreWeave is an enterprise cloud built specifically around NVIDIA GPUs for training and running the largest AI models, with a client list that includes OpenAI, Mistral AI, Google and IBM at production scale. It sells GPUs as 8-GPU node bundles rather than individual cards, which fits large training runs better than small experiments.
Pricing: Enterprise — on-demand H100 runs around $6.16/GPU-hour (sold as an 8-GPU node, roughly $49.24/hour total). Reserved capacity can cut that by up to 60%, spot instances run about 50% off, and storage has zero egress fees.
Strengths: trusted by major AI labs at genuine production scale; zero egress fees plus a free Kubernetes control plane; reserved capacity discounts of up to 60% off on-demand pricing.
Limits: on-demand pricing is notably higher than self-serve competitors like RunPod; GPUs are sold in 8-GPU node bundles, which is less flexible for smaller workloads; the enterprise positioning means less self-serve simplicity than a pay-as-you-go platform.
Nebius
Nebius is a European, publicly-traded (Nasdaq) cloud built specifically for AI workloads — GPU clusters, training and inference — aimed at companies that want serious AI compute without depending on a US hyperscaler. Being publicly traded means its financials are a matter of public record rather than a black box, which some enterprise buyers weigh heavily.
Pricing: Paid — H100 runs $2.15-$3.85/hour, H200 $2.45-$4.50/hour, and B200/B300 $3.95-$8.50/hour depending on preemptible vs. on-demand. CPU-only instances start at $0.05-$0.10/hour, with up to 35% off on reserved clusters (minimum spend $25).
Strengths: a sovereign European cloud with public-market financial transparency — a real alternative to US hyperscalers for compliance-sensitive buyers; published, transparent GPU pricing with no mandatory sales quote; an official NVIDIA partner with established customers like Shopify and Revolut.
Limits: its corporate history (spun out of Yandex) is worth understanding as part of vendor-risk evaluation; comparative TCO figures are self-reported and worth validating against your own workload; pricing generally runs higher than a pure marketplace like Vast.ai for raw compute.
Side-by-side
| CoreWeave | Nebius | |
|---|---|---|
| H100 on-demand | ~$6.16/GPU-hr (8-GPU node) | $2.15-$3.85/GPU-hr |
| GPU allocation | 8-GPU node bundles | Flexible, published per-GPU pricing |
| Track record | OpenAI, Mistral AI, Google, IBM in production | Shopify, Revolut; newer to the space |
| Corporate structure | US-based, private | European, publicly traded (Nasdaq) |
| Best for | Large-scale training runs needing proven enterprise infrastructure | Teams wanting transparent pricing or a non-US-hyperscaler option |
Other options worth checking
Both list similar names as alternatives worth comparing. RunPod is the self-serve, pay-by-the-second option — no contracts, sub-200ms serverless cold starts, and generally cheaper than either enterprise player, though availability during high-demand periods can be less predictable. Lambda scales from a single rented GPU up to superclusters exceeding 165,000 GPUs, with research-first roots dating to 2012, though its standard pricing doesn't clearly undercut RunPod's cheapest tiers. And Vast.ai is the marketplace model — anyone with spare GPU capacity can list it — which routinely runs 50%+ cheaper than traditional clouds, at the cost of more variable hardware quality.
Verdict
Pick CoreWeave if: you're running large-scale training and want infrastructure already proven at major AI labs, and node-level GPU bundles fit your workload.
Pick Nebius if: you want transparent, published per-GPU pricing, a European/non-US-hyperscaler option for compliance or sovereignty reasons, or you're evaluating a financially transparent, publicly-traded provider.
If price-per-GPU-hour is the deciding factor and you don't need CoreWeave's enterprise track record, Nebius's published rates are meaningfully lower for H100/H200 — but always validate real throughput and support responsiveness against your own workload before committing to a long-term contract.