Nebius

Nebius is a cloud service provider that offers infrastructure and platform services for Artificial Intelligence (AI) workloads, data-intensive applications, and general-purpose enterprise computing.

• Infrastructure-as-a-Service (IaaS) for compute, storage, and networking tailored to AI and high-performance workloads
• GPU-based AI infrastructure (AI infrastructure) for training and inference of Machine Learning (ML) models
• Managed platform services for data processing, application deployment, and workload orchestration (cloud platform services)
• Tools and services to support Machine Learning Operations (MLOps), Model Lifecycle Management (MLM), and AI development workflows (MLOps and AI tooling)
• Cloud resource management, access control, and cost governance capabilities for enterprise teams (cloud management and governance)

More About Nebius

Nebius provides cloud infrastructure and platform services oriented toward enterprises and organizations that run AI, data, and compute-intensive workloads. Its environment is positioned for technical teams that need Graphics Processing Unit (GPU) capacity for training and serving ML models, as well as CPU-based resources for traditional applications and services. Customers can provision virtual machines, storage, and networking resources and combine them with platform-level services to deploy applications in a controlled and programmable manner.

The Nebius platform includes GPU-based compute offerings (AI infrastructure) that are used for deep learning training, Large Language Model (LLM) workloads, and other parallelizable compute tasks. These GPU resources are typically accessed through virtualized instances with configurable profiles that align with common AI frameworks and toolchains. Enterprises can integrate these instances into their existing ML stacks, connecting to frameworks such as PyTorch or TensorFlow through standard APIs and SDKs, and using containerization technologies like Docker and orchestration frameworks like Kubernetes (container orchestration) where supported.

Beyond raw compute, Nebius offers cloud platform capabilities (cloud platform services) for developers and data teams. These may include managed services for data storage, object storage, and possibly databases, along with tools for workload scheduling and automation. Such services allow organizations to design architectures that separate storage, compute, and networking concerns, following patterns common in public cloud environments. Integration with Continuous Integration and Continuous Deployment (CI/CD) pipelines, Infrastructure-as-Code (IaC) tools, and monitoring systems enables teams to manage Nebius resources as part of a broader multi-cloud or hybrid-cloud strategy, when applicable.

For AI and MLOps teams, Nebius positions its environment as a place to run end-to-end model lifecycles, from experimentation and training to deployment and monitoring (MLOps and AI tooling). This typically involves support for model training jobs on GPU clusters, data preprocessing pipelines, experiment tracking, and deployment of models as APIs or services. Enterprises can use these capabilities to standardize how they develop, release, and operate AI features within applications, aligning with internal governance, security, and compliance requirements.

From a directory and marketplace perspective, Nebius aligns with categories such as public cloud infrastructure (IaaS), AI infrastructure, MLOps and AI tooling, and cloud platform services. It can be evaluated alongside other hyperscale or specialized cloud providers in areas like GPU availability, performance, pricing models, region and availability-zone topology, and integration with existing enterprise tooling. Its focus on AI and high-performance workloads places it within the AI infrastructure and cloud compute segments used by enterprises, research institutions, and technology-driven organizations.