# Nebius vs Qubinets

Nebius records 1,145,711 monthly visits with +10.7% month-over-month growth and Paid, Contact for Pricing pricing. Qubinets records 802 monthly visits with 0% growth and Freemium pricing.

| Metric | [Nebius](https://openaitools.app/tool/nebius) | [Qubinets](https://openaitools.app/tool/qubinets) |
| :--- | :--- | :--- |
| Website URL | https://nebius.com | https://qubinets.com |
| Categories | AI Developer Tools, AI Models, AI API, Open Source AI Models | AI Developer Tools, AI Agent, Large Language Models (LLMs), Open Source AI Models |
| Pricing Model | Paid, Contact for Pricing | Freemium |
| Monthly Visits | 1,145,711 | 802 |
| MoM Growth Rate | +10.7% | 0% |
| Primary Market | United States | Thailand |
| Direct Visits | 447,886 | 334 |
| Review Score | 4.5 | 4 |
| 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)

## Qubinets

Qubinets is aimed at the gap between wanting to run AI and big-data workloads on Kubernetes and actually assembling all the pieces. Standing up a data platform means choosing and wiring storage, compute, orchestration, pipelines and monitoring; Qubinets packages that into a more approachable layer so teams can deploy faster and spend less time on infrastructure plumbing.

Its positioning is cloud-native and open-source at the core, with paid and managed options layered on for teams that need more capacity or hands-on support. The website also markets it as a foundation for hosting AI agents and data pipelines, which places it in the broad ‘internal developer platform for AI’ category rather than as a single-purpose tool.

One caveat from this audit: qubinets.com did not respond from our crawlers, returning TLS handshake failures and closed connections across multiple attempts and independent fetchers, and the app subdomain failed DNS resolution. That pattern can indicate blocking or an outage rather than a permanent shutdown, so we are keeping the listing active but recommend confirming the current site, plans and terms directly with the vendor before relying on it.

**Pricing & Plans:** Freemium with paid and enterprise/managed tiers. A free or open-source core is offered, with paid plans and contact-based enterprise options layered on top. Because the site was unreachable during this audit, confirm exact pricing directly with the vendor.

- **Kubernetes AI infrastructure:** Get AI and big-data workloads running on Kubernetes without wiring every component by hand.
- **Data pipeline management:** Assemble and manage data pipelines that feed models and analytics workloads.
- **Open-source foundation:** An open-source core that teams can inspect, extend and self-host.
- **AI agent hosting:** Build and run AI agents alongside your infrastructure rather than as a separate silo.
- **Managed and paid tiers:** Managed and paid tiers add support, capacity and enterprise controls on top of the free core.

**Strengths:** Targets a genuinely painful problem: Kubernetes-based AI and data infrastructure; Open-source core avoids full vendor lock-in; Covers data pipelines and AI agents in one platform; Free tier lowers the cost of trying it

**Limitations:** Its own site was not reachable from our crawlers during this audit, so verify current pricing and availability directly; Kubernetes-based infrastructure still requires real operational understanding; Freemium tiers can impose resource or cluster limits; Managed/enterprise options are quote-based, so costs are not predictable up front

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

## Frequently Asked Questions

### How do Nebius and Qubinets compare in monthly traffic?

Nebius has 1,145,711 monthly visits, while Qubinets has 802. 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%; Qubinets has 0%.

### 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. Qubinets: Freemium. Freemium with paid and enterprise/managed tiers. A free or open-source core is offered, with paid plans and contact-based enterprise options layered on top. Because the site was unreachable during this audit, confirm exact pricing directly with the vendor.

## 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 | Features a peer-to-peer GPU rental marketplace with lower pricing, though with variable hardware reliability compared to managed infrastructure. | [.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 | Serverless cloud infrastructure for AI and data workloads | [.md](https://openaitools.app/tool/modal-com.md) |
| 6 | [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) |
| 7 | [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) |
| 8 | [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) |
| 9 | [Agent 37](https://openaitools.app/tool/agent-37) | 180,030 | +24.2% | Free Trial, Contact for Pricing | The low-cost cloud sandbox where AI agents actually live | [.md](https://openaitools.app/tool/agent-37.md) |
| 10 | [FluidStack](https://openaitools.app/tool/fluidstack) | 154,620 | +7.3% | Paid, Contact for Pricing | Specializes in large-scale enterprise data center GPU clusters for heavy training, though less tailored for instant serverless functions. | [.md](https://openaitools.app/tool/fluidstack.md) |

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Source: https://openaitools.app/compare/nebius-vs-qubinets

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