Table Of Contents

    Description

    Nebius provides a high-performance, AI-native cloud platform engineered for large-scale model training and demanding HPC workloads. Its architecture provides access to the latest NVIDIA GPUs connected by a high-speed InfiniBand fabric, designed to support massive, multi-node distributed training jobs efficiently. The platform is delivered as a managed service orchestrated via Kubernetes, accessible through modern APIs like Terraform, a CLI, and web consoles. To accelerate AI development, Nebius offers managed services for the MLOps lifecycle and data processing, all supported by a transparent, usage-based billing model and dedicated solution architects for enterprise teams.

    Customers

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    What Problem Does Nebius Solve?

    Accessing scalable, high-performance GPU infrastructure remains a major hurdle for AI teams, with long provisioning times, complex setup, and costly hardware slowing development. This bottleneck delays product development, increases time-to-market, and forces teams to compromise on model quality or abandon AI initiatives entirely. Nebius provides on-demand access to thousands of NVIDIA GPUs with pre-configured environments, allowing teams to scale from single GPUs to massive clusters instantly without upfront hardware costs.

    Pros

    • Scalable AI-Native Infrastructure:
      Nebius provides a fully integrated AI cloud platform optimized for NVIDIA GPUs (H100/H200/Blackwell) with Kubernetes or Slurm orchestration, enabling seamless scaling from single-node to supercluster deployments.
    • Efficient End-to-End ML Stack:
      Offers managed MLflow, Spark, high-throughput storage, and AI Studio for fine-tuning, batch inference, and playground experimentation with competitive per-token pricing.
    • Global High-Fidelity Data Center Network:
      Operates purpose-built data centers in Europe and expanding in the U.S., ensuring low latency, enterprise compliance (LPAR, VPN, GDPR), and native support for sensitive workloads.

    Cons

    • High Infrastructure Complexity:
      Deploying and managing InfiniBand networking, GPU orchestration, and ML pipelines requires significant DevOps and AI infrastructure expertise.
    • Ecosystem Narrowness:
      Focused on AI workloads, Nebius lacks complementary offerings like BI services, serverless compute, or general-purpose cloud-native tools.
    • Platform Maturity Risk:
      As a newer entrant with rapid scaling and evolving support/documentation, enterprises may encounter service gaps or slower incident response.

    Last updated: July 25, 2025

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