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Speeding up computational tasks is critical to push the boundaries of science and ensure scalability and efficiency. Check out how NVIDIA Hopper GPUs available on Nebius AI Cloud performed against CPU workflows to accelerate homology research, deep learning-enabled protein embeddings and ML clustering.

On March 13, 2025, a release of one of the control plane components of the VPC service in the eu-west1 region caused massive networking issues for clients' pods of Managed Services for Kubernetes.

We are excited to unveil our latest collaboration: Nebius AI Cloud, the ultimate cloud for AI innovators, and Outerbounds, an AI/ML platform powered by the popular open-source framework Metaflow, are now integrated as part of a broader technology partnership.

In February, we at Nebius were busy preparing several new data center regions and working on our large-scale participation in NVIDIA GTC. We also rolled out some improvements to the platform and contributions to open source — as well as new initiatives to support AI research: a brand new biotech award and a research credits program.

Generative AI and LLMs require immense computational power, making compute clusters essential for efficient scaling. Training and fine-tuning these models exceed the capacity of a single compute node, and parallel computing enables businesses to handle GenAI workloads at scale. In this article, we explore what compute clusters are and how to choose the right one for your needs.

Modern AI systems require substantial computational power to train and infer complex models. Cloud GPUs provide scalable infrastructure with high parallelism, offering access to virtualized GPUs through APIs and cloud platforms. The article delves into the technical aspects of cloud GPUs including virtualization, elastic scaling and management of high-performance workloads.

Images with pre-installed drivers in our Managed Service for Kubernetes enhance NVIDIA GPU cluster scalability and reduce compute node start-up time by 2-3x.

Preparing a GPU cluster requires some effort and careful attention from your engineering team. It can become a significant challenge in terms of deploying and configuring a compute environment. Today, we’re happy to announce a small yet meaningful enhancement that makes the cluster preparation process much easier and faster.

Repetitive employee queries can overwhelm HR departments and reduce time for strategic tasks. At Nebius, we implemented an AI Assistant powered by Nebius AI Studio that automates over 150 monthly queries. In this article, we explore how NLP and RAG help Studio drive such processes efficiency.