Blog

Launching biomolecular models at scale in a structured and safe environment is key for drug discovery teams to reach reliable, experimentally relevant insights faster. This article provides a practical, reproducible blueprint for running Boltz-2 inference in Nebius, from single-GPU experiments to scalable multi-node screening pipelines.

We’re proud to share the results of our participation in the MLPerf® Training v5.1 benchmark, where Nebius showcased strong performance across several configurations of the latest NVIDIA Blackwell and Blackwell Ultra systems. This round continues our commitment to transparency and collaboration with the MLCommons® community, as we work to ensure the highest quality standards for training and fine-tuning next-generation GenAI models.

Nebius and Anyscale have partnered to offer deeper platform integration and enable teams to deploy and scale Python and AI workloads with Ray easier, faster and cheaper. The partnership combines Nebius AI Cloud and Anyscale’s managed Ray platform, delivering a complete stack for developers and platform teams to move multimodal AI — across data processing (structured and unstructured), training and serving — from code to production.

This autumn has been one of acceleration for Nebius — from the rollout of the latest AI Cloud platform release to our brand new next-gen UK data center and the launch of Nebius Token Factory, an enterprise-grade inference platform.

Research on SWE agents involves building and running thousands of containers, quickly surpassing the limits of a single host. Our AI R&D team unveils the large-scale infrastructure that powers this research — the backbone behind recent releases such as SWE-rebench — and an open-source part of it to support the broader community.

We are introducing updates to the Nebius Status Board to enhance transparency during service outages and provide users with a clearer view of Nebius AI Cloud service availability.

We’re pleased to announce that Nebius AI Studio now hosts NVIDIA Nemotron Nano 2 VL, a compact, production-ready multimodal reasoning model engineered for real-world document intelligence and video understanding.

We’re launching Managed SkyPilot API Server on Nebius AI Cloud. It’s a fully managed service that transforms SkyPilot from a single-user tool into a shared platform where teams can pool resources, coordinate workloads and stop worrying about infrastructure operations.

Let’s explore one of the key features that makes the new NVIDIA GB200 NVL72 stand out: the fifth generation NVIDIA NVLink™ scale-up fabric. We’ll discuss how it redefines infrastructure by moving beyond the traditional 8-GPU NVLink. You’ll see a practical example of how to take advantage of this capability. Finally, we’ll examine a real-world use case: pre-training the Nemotron-4 340B LLM.

Today, we are thrilled to announce we achieved major security and compliance milestones. Independent third-party audits have verified that our security controls meet the requirements of SOC 2 Type II (including HIPAA), and align with the principles of NIS2 and DORA. We also obtained ISO 27001 certification, strengthened our practices by incorporating principles from ISO 27701, 27018, 27799, 27032, and standalone ISO 22301.

At Nebius, we’ve spent the past year working closely with enterprises that are moving AI projects from experiments to business-critical systems. The challenges they raise aren’t about “getting more GPUs” — they’re about how to govern, secure and scale AI infrastructure without creating bottlenecks for their teams. That’s the backdrop for our latest AI Cloud 3.0 release, named “Aether.”

Serving AI companies and enterprises with text-to-video inference is no small feat. These teams demand enterprise-ready performance — at scale, with low latency, and high reliability. In this post, we’ll unpack the state-of-the-art engineering that enables Nebius and Baseten to deliver production-grade video generation — and show you how to test it yourself.