# Nebius vs Sesterce Cloud

Nebius records 1,145,711 monthly visits with +10.7% month-over-month growth and Paid, Contact for Pricing pricing. Sesterce Cloud records 2,158 monthly visits with -82% growth and Paid pricing.

| Metric | [Nebius](https://openaitools.app/tool/nebius) | [Sesterce Cloud](https://openaitools.app/tool/sesterce-cloud) |
| :--- | :--- | :--- |
| Website URL | https://nebius.com | https://cloud.sesterce.com |
| Categories | AI Developer Tools, AI Models, AI API, Open Source AI Models | AI Developer Tools |
| Pricing Model | Paid, Contact for Pricing | Paid |
| Monthly Visits | 1,145,711 | 2,158 |
| MoM Growth Rate | +10.7% | -82% |
| Primary Market | United States | Netherlands |
| Direct Visits | 447,886 | 594 |
| Review Score | 4.5 | 4.3 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## Nebius

Nebius positions itself as "the ultimate AI cloud," an infrastructure stack engineered specifically for AI workloads rather than adapted from general-purpose cloud. The core of the platform is raw GPU capacity from NVIDIA — including GB300 NVL72, HGX B300, GB200 NVL72, HGX B200, H200, H100, RTX PRO 6000, and L40S — delivered as non-virtualized instances attached to InfiniBand networking. Above that sit managed services such as Kubernetes, Soperator (Slurm on Kubernetes), PostgreSQL, and MLflow, so teams get the orchestration and experimentation tooling that large training runs need without assembling it themselves.

On the inference side, Nebius offers Token Factory, a managed endpoint for running open and frontier models, alongside serverless compute options. Storage is available as shared filesystems, WEKA, block volumes, and tiered object storage, all priced transparently by the gigabyte. Consumption is flexible: customers can pay on-demand, use preemptible and spot capacity at market-driven prices, or reserve capacity through commitments for lower rates. Networking egress, public IPs, and Kubernetes management are listed as free, which simplifies capacity planning.

Nebius supports the full lifecycle — pre-training, post-training, and inference — and publishes customer stories spanning financial services, healthcare, robotics, media, and e-commerce. Because the company also operates its own data centers and hardware supply chain, it can offer capacity guarantees and support arrangements that are hard to match on repurposed public cloud. Pricing is usage-based and published on the site, with contact needed for large clusters and enterprise agreements.

**Pricing & Plans:** Usage-based pricing published on the site. On-demand GPU instances range from roughly $1.55/GPU-hour for L40S up to about $9.50/GPU-hour for HGX B300, with preemptible and live spot options starting around $0.79/GPU-hour. CPU-only instances start near $0.06/cpu-hour, managed Kubernetes and networking are free, and large-scale clusters or commitments are quoted through sales.

- **Non-virtualized GPU clusters:** Bare-metal access to NVIDIA GB300, B300, GB200, B200, H200, H100, RTX PRO 6000, and L40S GPUs connected over InfiniBand for training and inference at scale.
- **Nebius Token Factory:** A managed inference service for running popular open and frontier models through an API, so applications can add LLM capabilities without owning GPUs.
- **Managed MLOps services:** Built-in Kubernetes, Soperator for Slurm jobs, PostgreSQL, and MLflow give teams a ready-made environment for orchestration, tracking, and experiments.
- **Flexible consumption and spot pricing:** Choose on-demand, preemptible, or live market-driven spot capacity, or commit to reserved clusters for discounts on long-running workloads.
- **Scalable AI storage:** Shared filesystems, WEKA, block volumes, and tiered object storage sized for multi-hundred-terabyte training datasets.

**Strengths:** Transparent, publicly listed per-hour GPU and storage pricing; Broad NVIDIA lineup from L40S up to GB300 NVL72; Free Kubernetes management, networking egress, and public IPs; Integrated MLOps tooling including MLflow, Slurm via Soperator, and PostgreSQL

**Limitations:** Top-end clusters like GB300 and GB200 are quote-only, not self-serve; Spot and preemptible capacity is interruptible and prices move with demand; Requires meaningful ML infrastructure knowledge to get the most out of it

[Profile (Markdown)](https://openaitools.app/tool/nebius.md)

## Sesterce Cloud

Sesterce Cloud is a GPU-focused cloud platform that lets teams rent high-performance accelerators by the hour instead of buying hardware. Its catalog covers datacenter and consumer GPUs — H200, H100, A100 (40GB and 80GB), GAUDI2, RTX Pro 6000, RTX 5090, RTX 4090, L40/L40S, A6000, A5000, A4000, A40, L4, A10 and V100 among them — alongside CPU-only instances for lighter jobs.

Beyond single machines, the platform supports bare-metal servers, spot offers and multi-GPU cluster configurations, with combinations such as 8x H100, 8x A100, 1x to 8x RTX 5090 and 8x GAUDI2 listed with their combined vRAM, vCPU and system RAM. Pricing is displayed per hour of compute, and persistent volumes let you keep datasets and checkpoints between sessions. Documentation and an API reference support programmatic provisioning.

The positioning is a European, high-performance and energy-conscious alternative to hyperscaler GPU capacity, aimed at AI training, inference, generative AI and HPC workloads. Because the platform publishes hardware, region and hourly rate together, it suits teams that want to compare cost and location before committing.

**Pricing & Plans:** Hourly, on-demand pricing without commitment for standard instances, with rates published per GPU model on the compute page. Cluster and bare-metal configurations are quoted by their combined hardware. Check the platform for current rates.

- **On-Demand GPU Instances:** Deploy single-GPU or multi-GPU instances in minutes from a public catalog of H200, H100, A100, GAUDI2, RTX and L40S hardware.
- **Bare Metal and Clusters:** Reserve bare-metal nodes and multi-GPU clusters with dedicated vRAM, vCPU and RAM for large training runs.
- **Transparent Hourly Pricing:** Every GPU class is listed with an hourly rate and available regions, so you can compare cost before launching.
- **Persistent Storage and API:** Attach persistent volumes, use the documented API and manage everything from a single web console.
- **Broad Hardware Selection:** Choose from consumer and datacenter accelerators including Gaudi and RTX cards to match budget and workload.

**Strengths:** Wide accelerator selection from RTX consumer cards up to H200 and GAUDI2; Hourly on-demand pricing with rates shown up front; Bare-metal and multi-GPU clusters for large training runs; European provider positioning with API and documentation available

[Profile (Markdown)](https://openaitools.app/tool/sesterce-cloud.md)

## Frequently Asked Questions

### How do Nebius and Sesterce Cloud compare in monthly traffic?

Nebius has 1,145,711 monthly visits, while Sesterce Cloud has 2,158. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Nebius has a month-over-month growth rate of +10.7%; Sesterce Cloud has -82%.

### How does pricing compare?

Nebius: Paid, Contact for Pricing. Usage-based pricing published on the site. On-demand GPU instances range from roughly $1.55/GPU-hour for L40S up to about $9.50/GPU-hour for HGX B300, with preemptible and live spot options starting around $0.79/GPU-hour. CPU-only instances start near $0.06/cpu-hour, managed Kubernetes and networking are free, and large-scale clusters or commitments are quoted through sales. Sesterce Cloud: Paid. Hourly, on-demand pricing without commitment for standard instances, with rates published per GPU model on the compute page. Cluster and bare-metal configurations are quoted by their combined hardware. Check the platform for current rates.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [fal.ai](https://openaitools.app/tool/fal-ai) | 3,093,684 | -3.7% | Paid, pay-as-you-go usage-based pricing | Tailored specifically for high-throughput generative media inference pipelines, whereas Nebius targets general GPU compute infrastructure. | [.md](https://openaitools.app/tool/fal-ai.md) |
| 2 | [RunPod](https://openaitools.app/tool/runpod) | 2,881,043 | +5.9% | Paid | The AI developer cloud for GPU pods, serverless inference and clustering | [.md](https://openaitools.app/tool/runpod.md) |
| 3 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Provides robust serverless inference APIs and GPU clusters for open-source models, but with less emphasis on raw bare-metal control. | [.md](https://openaitools.app/tool/together-ai.md) |
| 4 | [Vast.ai](https://openaitools.app/tool/vast-ai) | 1,257,554 | +2.8% | Paid | Rent cloud GPUs by the second from a global marketplace | [.md](https://openaitools.app/tool/vast-ai.md) |
| 5 | [Modal](https://openaitools.app/tool/modal-com) | 1,196,021 | +30.2% | Freemium, Contact for Pricing | Executes Python workloads and model inference in serverless containers effortlessly, but lacks bare-metal cluster management. | [.md](https://openaitools.app/tool/modal-com.md) |
| 6 | [Salad](https://openaitools.app/tool/salad-gpu-cloud) | 713,519 | +10.4% | Free Trial, Paid, Contact for Pricing | Distributed GPU cloud that orchestrates the world's idle consumer GPUs | [.md](https://openaitools.app/tool/salad-gpu-cloud.md) |
| 7 | [DeepInfra](https://openaitools.app/tool/deep-infra) | 457,810 | -8.9% | Paid | Provides exceptionally cheap serverless inference for open models via API, but does not offer raw bare-metal GPU rentals. | [.md](https://openaitools.app/tool/deep-infra.md) |
| 8 | [Lightning AI](https://openaitools.app/tool/lightning-ai) | 272,562 | -12.3% | Freemium, Paid, Contact for Pricing | The AI cloud built by the creators of PyTorch Lightning | [.md](https://openaitools.app/tool/lightning-ai.md) |
| 9 | [Novita AI](https://openaitools.app/tool/novita-ai) | 271,371 | -10.4% | Paid | Combines model APIs and serverless GPU jobs, but lacks the enterprise-grade bare-metal infrastructure orchestration of Nebius. | [.md](https://openaitools.app/tool/novita-ai.md) |
| 10 | [FluidStack](https://openaitools.app/tool/fluidstack) | 154,620 | +7.3% | Paid, Contact for Pricing | Gigawatt-scale AI compute, built and operated end to end | [.md](https://openaitools.app/tool/fluidstack.md) |

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Source: https://openaitools.app/compare/nebius-vs-sesterce-cloud

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