Nebius is a global cloud platform purpose-built for **production AI**. It combines custom hardware, proprietary software, and energy‑efficient data centers to power modern AI workloads—from the silicon all the way up to your applications. It’s designed for a wide range of users and AI maturity levels, including:

• ML engineers who are experimenting with models, training from scratch, or fine‑tuning existing ones (including open source models).
• AI product managers who need to power applications with AI without getting bogged down in infrastructure details.
• DevOps and platform teams who manage hybrid infrastructure and want predictable performance and reliability for AI workloads.

Nebius aims to give you the **performance of a supercomputer with the flexibility of a cloud**, so you can run everything from early experimentation to large‑scale training and global inference on the same platform.

Nebius is built to support **any AI workflow** while helping teams manage and optimize total cost of ownership (TCO). You can choose how close to the metal you want to work:

• Raw GPU compute for teams that want full control over training and infrastructure.
• ML tooling and platforms such as Managed MLflow, JupyterLab, Ray/Anyscale, ComfyUI, and a model hub to streamline experiments and model lifecycle.
• Serverless and managed inference so you can deploy models via simple APIs without managing GPUs or orchestration.

Nebius is designed to deliver **lower TCO** for both fine‑tuning and inference compared to AWS, based on a recent TCO study by SemiAnalysis (“Calculating the Total Cost of a GPU Cluster,” March). The platform focuses on:

• High‑density, cost‑efficient GPU clusters for training and inference.
• Integrated tooling that reduces time spent stitching together infrastructure.
• Support for open source models and industry‑specific stacks, so you can reuse what you already have.

This combination helps teams move from experimentation to production while keeping infrastructure spend more predictable and aligned with usage.

Nebius is built as an end‑to‑end AI/ML platform for **real‑world AI at scale**, with a focus on both performance and operational reliability. Core infrastructure

• NVIDIA GPU servers including high‑scale configurations like GB300 NVL72 and GB200 NVL72.
• CPU‑only servers for supporting services and non‑GPU workloads.
• High‑performance networking with NVIDIA NDR/XDR InfiniBand for training and inference clusters.
• Compute and GPU clusters, virtual machines, containers, and Managed Kubernetes.
• Storage options including block volumes, object storage, shared filesystems, and managed Soperator.

AI/ML platform capabilities

• AI ops, ML ops, and Data ops tooling.
• Token Factory for fine‑tuning open source models and combining them with agentic search.
• Serverless orchestration and managed endpoints for deploying models via APIs.
• Support for NVIDIA NIMs, SkyPilot, dstack, ComfyUI, Ray, and Anyscale.

Reliability, security, and support

• Auto‑healing GPU clusters with InfiniBand networking for running production AI with confidence.
• Built‑in observability, audit logs, and secrets management.
• Security and compliance integrated into the platform, not just a bare‑metal setup.
• Fast, white‑glove 24×7 support from real humans, with a focus on short First Response Time (FRT) for critical incidents and strong Mean Time To Resolution (MTTR) for non‑escalated cases.

Nebius has been recognized with NVIDIA Exemplar Cloud Partner status, and is delivered as a true cloud platform. This makes it suitable for teams that want to scale AI workloads on a rapidly expanding global infrastructure while maintaining operational control and visibility.