Nebius

Nebius is an AI-native cloud platform providing cost-effective GPU infrastructure and managed Kubernetes. Their services are optimized for training large-scale AI models and demanding high-performance computing (HPC) workloads.

Specialization:
AI Cloud Infrastructure, GPU Computing, High-Performance Computing (HPC), Managed Kubernetes, Distributed Training, AI Model Hosting

Company Type:
Startup

Total Financing Amount:
$700M

Founded Date:
Sep 6, 2022

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

Chatfuel, Krisp, Dubformer, LIMS, Recraft

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