Nebius is built for large training runs. Eight GPU configurations, all data-center class, wired for cluster scale, with managed Slurm and managed Kubernetes offered at no software cost. That is a deliberate product for a specific customer, and for that customer it is a strong one.
Runpod is built for the whole arc of an AI project: a persistent box to develop on, an endpoint that scales to zero when nobody is calling it, and a cluster when a job outgrows one node. Same account, same container images.
The two overlap on hardware and diverge almost everywhere else. Here is where each is actually the better tool.
Where Nebius is the better tool
Managed Slurm, free. Soperator runs Slurm on Kubernetes and Nebius charges nothing for the software. If your research team already thinks in sbatch scripts and job queues, having that operated for you rather than stood up yourself is a real reason to pick a provider, and Runpod has no equivalent.
Managed Kubernetes, also free. Same story. If your orchestration is already Kubernetes-shaped, that removes a whole layer of work.
Rack-scale systems. GB200 NVL72 and GB300 NVL72 are on their menu. If you are training at a scale where 72 GPUs in one NVLink domain is the right unit, that is a conversation Nebius can have.
A published interruptible tier for checkpointed work. Every card except the two rack-scale systems carries a preemptible rate alongside the on-demand rate. For a training job that checkpoints and restarts cleanly, that is the right way to buy compute and the rates are aggressive.
If most of that paragraph describes your team, use Nebius. Nothing below changes that.
Where the catalog stops
Nebius sells eight configurations and the cheapest is an L40S. That is the floor, and it has consequences beyond price.
There is no A100 at all. Not PCIe, not SXM. The A100 remains one of the most practical cards for fine-tuning and mid-size inference, and it is simply absent from their lineup. Runpod publishes both, at {{gpu:a100-pcie}}/hr and {{gpu:a100-sxm}}/hr on Secure Cloud.
Nothing consumer-class or entry-level. No RTX 4090, 5090, A5000, A40 or L4. If you are prototyping, running embeddings, doing batch image work or serving a small model, the smallest thing Nebius will rent you is an L40S. Runpod publishes ten models below that tier, down to {{gpu:rtx-a5000:community}}/hr on Community Cloud.
This is a positioning choice on their part rather than a gap they overlooked. They are not trying to serve the person prototyping on a 4090. It just means that person is not their customer.
What Runpod covers that Nebius does not
Serving with scale-to-zero. Nebius rents instances, which bill continuously. Runpod Serverless scales to zero between requests with sub-200ms cold starts via FlashBoot, so an endpoint with uneven traffic is not paying through its quiet hours. For inference workloads that is a structural difference, not a discount.
Clusters without a sales call. Nebius's largest systems are contact-sales, and commitment discounts are negotiated. Runpod Instant Clusters provision from the console, no contract, at {{cluster:h200-sxm}}/hr for H200 SXM and {{cluster:a100-sxm}}/hr for A100 SXM. If you want a multi-node job running this afternoon rather than after a procurement cycle, that is the difference.
One environment across the whole project. Develop on a Pod, deploy the same image to Serverless, train on a Cluster. Nothing gets rebuilt when the workload changes shape.
Reach and breadth. 24 GPU models against eight, across 31 global regions, plus SOC 2 Type II.
Pricing
Nebius publishes two rates for every card. The preemptible tier undercuts Runpod Community Cloud across the overlap. The on-demand tier mostly does not.
The preemptible advantage is real and you should take it if your job tolerates eviction. On the on-demand tier the picture largely inverts, with one close call: their H200 and Runpod Secure Cloud land within cents of each other, so decide that one on region and tooling rather than on price.
Nebius also offers commitment discounts of up to 35% off on-demand for multi-month reservations of large clusters, arranged through sales. All their rates exclude VAT.
Which one should you choose
Choose Nebius if you are running large checkpointable training jobs that can use preemptible capacity, if you want managed Slurm or Kubernetes operated for you at no software cost, if you need rack-scale NVL72 systems, or if you are committing to a multi-month cluster reservation.
Choose Runpod if your project involves anything other than large training runs: serving with uneven traffic, prototyping on a smaller card, fine-tuning on an A100, or spinning up a cluster today without a procurement cycle.
The distinction is job shape, not vendor quality. Nebius made a deliberate choice to serve large-scale training on a narrow, high-end lineup, and they serve it well. Runpod is the AI developer cloud, covering development on Pods, serving on Serverless and training on Instant Clusters, across a range that starts far below where Nebius begins.
Frequently asked questions
What is the main difference between Runpod and Nebius?
Scope and focus. Nebius offers eight high-end GPU configurations with free managed Slurm and Kubernetes, aimed at large-scale training. Runpod covers development on Pods, serving on Serverless and training on Instant Clusters across 24 GPU models, on one account with the same container images.
Does Nebius have A100s?
No. Their public lineup runs GB300, B300, GB200, B200, H200, H100, RTX PRO 6000 and L40S. Runpod publishes A100 PCIe at {{gpu:a100-pcie}}/hr and A100 SXM at {{gpu:a100-sxm}}/hr on Secure Cloud.
Does Nebius offer serverless GPUs?
Nebius lists a Serverless AI product on their site, but no per-request rate appears on their public pricing page. Runpod Serverless publishes per-GPU hourly rates and scales to zero between requests with sub-200ms cold starts via FlashBoot.
What does preemptible mean on Nebius?
The instance can be reclaimed when capacity is needed elsewhere. It suits training runs that checkpoint and restart, and does not suit interactive work or production serving. Nebius lists preemptible and on-demand rates side by side for every GPU except their two contact-sales rack-scale systems.
Which is better for multi-node training?
Both are credible, for different reasons. Nebius offers free managed Slurm and Kubernetes and rack-scale NVL72 systems arranged through sales. Runpod Instant Clusters provision self-serve from the console at {{cluster:h200-sxm}}/hr for H200 SXM, with no contract. Pick on whether you want the tooling managed or the cluster running in minutes.
Is Nebius cheaper than Runpod?
On preemptible capacity, for the cards both offer, yes. Their preemptible H100 SXM is $2.15/hr and H200 is $2.45/hr, both below Runpod Community Cloud. On on-demand capacity it mostly runs the other way, and below an L40S there is nothing to compare because Nebius does not sell anything smaller.
Do either charge for data transfer?
Neither does. Nebius lists egress and ingress traffic and public IP addresses as free. Runpod charges no ingress or egress fees either.
