# ClawCloud Run vs Nebius

ClawCloud Run records 4,690 monthly visits with -27.1% month-over-month growth and Freemium pricing. Nebius records 1,145,711 monthly visits with +10.7% growth and Paid, Contact for Pricing pricing.

| Metric | [ClawCloud Run](https://openaitools.app/tool/clawcloud-run) | [Nebius](https://openaitools.app/tool/nebius) |
| :--- | :--- | :--- |
| Website URL | https://run.claw.cloud/?referralCode=Q7T3Y8M4K6VX | https://nebius.com |
| Categories | AI Developer Tools, AI Workflow, No-Code&Low-Code | AI Developer Tools, AI Models, AI API, Open Source AI Models |
| Pricing Model | Freemium | Paid, Contact for Pricing |
| Monthly Visits | 4,690 | 1,145,711 |
| MoM Growth Rate | -27.1% | +10.7% |
| Primary Market | China | United States |
| Direct Visits | 2,521 | 447,886 |
| Review Score | 4.1 | 4.5 |
| Saved Count | 3 | 0 |
| Supported Platforms | Website | Website |

## ClawCloud Run

ClawCloud Run sits in the platform-as-a-service space, aiming to remove the friction between "I have a container image" and "my app is live on the internet." Instead of hand-writing Kubernetes manifests, configuring ingress, or wiring up persistent storage, users point the platform at a Docker image, a Git repository, or a prebuilt template and let ClawCloud handle scheduling, scaling, TLS certificates, and networking. The interface is browser-based, so deployment does not depend on a specific local toolchain.

The platform leans on well-understood cloud-native building blocks. Applications run on managed Kubernetes, so workloads inherit container isolation, health checks, rolling updates, and horizontal scaling. Integrated CI/CD and GitOps-style workflows let teams connect a repository and ship new versions automatically on every commit, keeping the deployment history auditable. A catalog of one-click templates covers common open-source services such as databases, caches, and self-hosted tools, which shortens the setup time for supporting infrastructure.

ClawCloud Run positions itself as a lower-cost alternative to mainstream cloud hosts, offering a free trial credit to get started and usage-based pricing thereafter. It is best suited to developers who are comfortable with containers but do not want to become Kubernetes operators, and to teams that value fast iteration over deep infrastructure control.

**Pricing & Plans:** Freemium. New users typically receive a small free trial credit (reported around $5) to explore deployments, after which usage is billed according to consumed compute, memory, and storage resources. Because the landing page could not be reached during this review, check the official site for current plan details and regional availability.

- **One-click container deployment:** Launch a Docker image, a Git repository, or a catalog template and get a running service with a public URL, without authoring Kubernetes manifests.
- **Managed Kubernetes under the hood:** Workloads run on managed clusters that provide isolation, health checks, rolling updates, and horizontal scaling out of the box.
- **Integrated CI/CD and GitOps workflows:** Connect a repository so every commit can trigger a build and a versioned rollout, with rollback to a previous release when something breaks.
- **Templates and managed databases:** A curated catalog of common open-source services and database engines lets you stand up supporting infrastructure in a few clicks.
- **Built-in networking and TLS:** Public endpoints, custom domains, and HTTPS certificates are provisioned automatically, removing the usual ingress and certificate chores.

**Strengths:** Removes most Kubernetes and DevOps busywork for small teams; Container-based, so existing Docker images and workflows carry over; Git-driven deployment makes releases repeatable and auditable; Template catalog speeds up common infrastructure setup

**Limitations:** The site was unreachable during this review, so current feature and pricing details could not be confirmed; Requires some familiarity with containers and environment variables; Less fine-grained control than running your own Kubernetes cluster

[Profile (Markdown)](https://openaitools.app/tool/clawcloud-run.md)

## 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)

## Frequently Asked Questions

### How do ClawCloud Run and Nebius compare in monthly traffic?

ClawCloud Run has 4,690 monthly visits, while Nebius has 1,145,711. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

ClawCloud Run has a month-over-month growth rate of -27.1%; Nebius has +10.7%.

### How does pricing compare?

ClawCloud Run: Freemium. Freemium. New users typically receive a small free trial credit (reported around $5) to explore deployments, after which usage is billed according to consumed compute, memory, and storage resources. Because the landing page could not be reached during this review, check the official site for current plan details and regional availability. 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.

## 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 | Offers flexible on-demand GPU rentals and serverless pods, but focuses more on flexible developer instances than turnkey enterprise clusters. | [.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 | 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 | [MyClaw](https://openaitools.app/tool/myclaw) | 990,387 | -23.8% | Paid | Your always-on AI teammate, hosted and managed for you | [.md](https://openaitools.app/tool/myclaw.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 | [Zeabur](https://openaitools.app/tool/zeabur) | 275,642 | -15.9% | Free Trial, Paid | AI DevOps engineer that deploys and scales your apps | [.md](https://openaitools.app/tool/zeabur.md) |
| 9 | [Lightning AI](https://openaitools.app/tool/lightning-ai) | 272,562 | -12.3% | Freemium, Paid, Contact for Pricing | Provides interactive development studios and on-demand GPUs for training, but focuses more on PyTorch workflows than raw infrastructure. | [.md](https://openaitools.app/tool/lightning-ai.md) |
| 10 | [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) |

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Source: https://openaitools.app/compare/clawcloud-run-vs-nebius

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