# Inquir Compute vs Nebius

Inquir Compute records 769 monthly visits with -59.1% 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 | [Inquir Compute](https://openaitools.app/tool/inquir) | [Nebius](https://openaitools.app/tool/nebius) |
| :--- | :--- | :--- |
| Website URL | https://inquir.org | https://nebius.com |
| Categories | AI Search Engine, AI Chatbot, AI API, No-Code&Low-Code | AI Developer Tools, AI Models, AI API, Open Source AI Models |
| Pricing Model | Freemium | Paid, Contact for Pricing |
| Monthly Visits | 769 | 1,145,711 |
| MoM Growth Rate | -59.1% | +10.7% |
| Primary Market | Global | United States |
| Direct Visits | 305 | 447,886 |
| Review Score | 3.8 | 4.5 |
| Saved Count | 1 | 0 |
| Supported Platforms | Website | Website |

## Inquir Compute

Inquir Compute is a cloud platform for running applications, positioned as an alternative to platforms like Railway, Render, Fly.io, Vercel Functions and AWS Lambda. The workflow follows a pattern developers already know: connect a repository or container image, let the platform build it, then promote the release to production. It also keeps the previous release around as a reserve for quick rollbacks.

What distinguishes it is how much it packs into a single project. Container apps, serverless functions, scheduled pipelines, background workers and databases all live side by side, connected over a private network rather than the public internet. You can provision PostgreSQL with pgvector for embeddings, Redis for caching, and MongoDB or MySQL as needed, and wire them to your services without external exposure. Observability panels cover memory, CPU, request latency and network egress so you can spot a service nearing its limits and add replicas.

Access is flexible: a web console with an integrated editor, an Inquir CLI for deploying functions and containers from the terminal, and MCP-based deployment from AI coding tools like Claude Code, Cursor and Codex. The platform is priced in roubles with a 14-day free trial, Simple and Pro subscription tiers, and an Enterprise/on-premise option for organizations that need it in their own infrastructure.

**Pricing & Plans:** Paid with a free trial. A 14-day free trial is available without a card (once per account). Simple is 590 roubles/month and Pro is 2,490 roubles/month (yearly billing gives two months free), while Enterprise/On-Premise is a custom quote. Prices are in roubles and payment is handled through the platform's payment provider.

- **Dockerfile and container deploys:** Deploy from a Dockerfile or container image; Inquir builds the image, cuts a release and switches traffic when readiness checks pass.
- **Private networking:** Bring apps, functions and databases into one project and let them talk over an internal network instead of the public internet.
- **Serverless functions and pipelines:** Run synchronous and asynchronous functions, scheduled jobs and pipelines with run history, including background processing for web apps.
- **Managed databases:** Provision PostgreSQL (with pgvector), Redis, MongoDB and MySQL alongside your services, complete with persistent volumes.
- **Observability and scaling:** Watch memory, CPU, network and latency, then add replicas when an app approaches its limits.
- **CLI, IDE and API access:** Deploy from the web console, the Inquir CLI or AI coding agents over MCP, with custom domains and API key auth for serverless functions.

**Strengths:** Apps, functions, pipelines and databases managed together in one project with private networking; Deploy from Dockerfile or container image, with rollback to the previous release; Managed PostgreSQL with pgvector, Redis, MongoDB and MySQL included; Observability and replica scaling built in, plus CLI and MCP-based deployment

**Limitations:** Interface and pricing are currently oriented toward Russian-speaking users and local payment methods; Public prices are in roubles and card payments were rolling out gradually at the time of review; Less aimed at casual/free users, since the free tier is a 14-day trial rather than a permanent plan; Managed hosting means less low-level control than running your own servers

[Profile (Markdown)](https://openaitools.app/tool/inquir.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 Inquir Compute and Nebius compare in monthly traffic?

Inquir Compute has 769 monthly visits, while Nebius has 1,145,711. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Inquir Compute has a month-over-month growth rate of -59.1%; Nebius has +10.7%.

### How does pricing compare?

Inquir Compute: Freemium. Paid with a free trial. A 14-day free trial is available without a card (once per account). Simple is 590 roubles/month and Pro is 2,490 roubles/month (yearly billing gives two months free), while Enterprise/On-Premise is a custom quote. Prices are in roubles and payment is handled through the platform's payment provider. 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 | [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) |
| 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/inquir-vs-nebius

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