# Agent 37 vs Nebius

Agent 37 records 180,030 monthly visits with +24.2% month-over-month growth and Free Trial, Contact for Pricing pricing. Nebius records 1,145,711 monthly visits with +10.7% growth and Paid, Contact for Pricing pricing.

| Metric | [Agent 37](https://openaitools.app/tool/agent-37) | [Nebius](https://openaitools.app/tool/nebius) |
| :--- | :--- | :--- |
| Website URL | https://www.agent37.com | https://nebius.com |
| Categories | AI Coaching, AI Agent, AI Developer Tools, Large Language Models (LLMs) | AI Developer Tools, AI Models, AI API, Open Source AI Models |
| Pricing Model | Free Trial, Contact for Pricing | Paid, Contact for Pricing |
| Monthly Visits | 180,030 | 1,145,711 |
| MoM Growth Rate | +24.2% | +10.7% |
| Primary Market | Paraguay | United States |
| Direct Visits | 72,672 | 447,886 |
| Review Score | 4.3 | 4.5 |
| Saved Count | 0 | 0 |
| Supported Platforms | Website | Website |

## Agent 37

Agent 37 is a cloud infrastructure product aimed at people who need somewhere real for AI agents to run. Instead of a chat window, every customer gets a sandbox: an isolated Linux container with CPU, memory, persistent disk, an optional public HTTPS URL, and outbound network access. The company positions itself primarily on price, claiming its sandboxes cost roughly 94% less than most competing providers and publishing a comparison table against AWS, Daytona, E2B, Modal, Vercel, and others. Billing is prepaid and metered by the minute — vCPU, memory, and disk each have their own unit rate — with no subscription fee.

Beyond raw compute, Agent 37 ships a layer of agent-specific conveniences. You can start from a ready-made harness such as Claude Code, Codex, OpenClaw, OpenCode, or Hermes, or bring your own Docker image. Agents keep their files across sleep, stop and restart cycles, and can be given cron schedules so they run unattended and simply report results. Model access can come from the platform gateway (Claude, OpenAI, Gemini, Grok) or from your own API keys, and integrations cover services such as Gmail, Slack, Notion, and GitHub through a Composio-based connector catalog, plus metered access to paid tools like web scraping and people/company data.

Security is a major part of the pitch: sandboxes are isolated with gVisor, hosts have no public hostname, ingress goes through Cloudflare with API-key authentication, and outbound traffic is restricted to the public internet. The company states it does not collect prompts, files, or terminal sessions, holds SOC 2 Type I, and is working toward Type II. It also offers startup credits and a free personal agent tier for individuals who just want an agent of their own.

**Pricing & Plans:** Prepaid, pay-as-you-go compute metered per minute with no subscription or minimum. New accounts get a $5 starter credit once a card is on file, and the company advertises up to $10,000 in credits for startups. Exact unit rates are published on the pricing page and change over time, so confirm current figures there.

- **Per-minute sandbox billing:** Pay for vCPU, memory and disk separately while the sandbox runs; when it sleeps or is deleted the compute meter stops and you are left with disk cost only.
- **Ready-made agent harnesses:** Launch Claude Code, Codex, OpenClaw, OpenCode, Hermes, Grok or your own Docker image, each in its own tenant-isolated sandbox.
- **Persistent workspace and scheduling:** Files survive sleep, restarts and weeks of inactivity, and agents can be attached to cron-style schedules so work runs unattended.
- **Networking and custom domains:** Expose individual ports publicly, attach your own domain, or keep everything behind an API key on an authenticated URL.
- **Integrations and metered tools:** Connect 1,000+ apps such as Gmail, Slack, Notion and GitHub, and buy one-off capabilities like scraping or enrichment from the same balance.

**Strengths:** Aggressively low per-minute pricing with an explicit public comparison against major sandbox providers; Persistent disk and scheduling make it suitable for real agent workloads rather than one-shot tasks; Strong isolation story (gVisor, firewalled egress, no public hostnames) plus SOC 2 Type I; Flexible model and tool sourcing: platform gateway, bring-your-own keys, or pay-per-use tools

**Limitations:** Prepaid balance model means you must top up in advance and monitor spend across many sandboxes; Persona pricing and plan details are only available after contacting the team for the white-label and enterprise tracks; Documentation and benchmark claims are largely self-published, so independent verification is limited

[Profile (Markdown)](https://openaitools.app/tool/agent-37.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 Agent 37 and Nebius compare in monthly traffic?

Agent 37 has 180,030 monthly visits, while Nebius has 1,145,711. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Agent 37 has a month-over-month growth rate of +24.2%; Nebius has +10.7%.

### How does pricing compare?

Agent 37: Free Trial, Contact for Pricing. Prepaid, pay-as-you-go compute metered per minute with no subscription or minimum. New accounts get a $5 starter credit once a card is on file, and the company advertises up to $10,000 in credits for startups. Exact unit rates are published on the pricing page and change over time, so confirm current figures there. 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 | [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 | [Browserbase](https://openaitools.app/tool/browserbase) | 283,597 | -8% | Freemium | Cloud browsers and web APIs for AI agents | [.md](https://openaitools.app/tool/browserbase.md) |
| 8 | [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) |
| 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 | 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/agent-37-vs-nebius

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