Blog

After completing a full rewrite of our cloud from the ground up in October, we began improving the foundation that we brought to the market. The features and tools we have introduced since then span our entire range of cloud services, from Compute Cloud to managed MLOps solutions.

Prompt engineering has advanced considerably in the last three years. This article overviews the process and includes several beginner and advanced strategies to help AI teams get the most out of their LLM models.

As the holiday season approaches and we all juggle year-end projects, we’re excited to bring you a gift of expanded capabilities on Nebius AI Studio. These updates — including advanced vision models, a broader range of language models, powerful embeddings and LoRA hosting — are designed to help you jumpstart the new year with stronger, more versatile AI tools.

Metrics provide a mathematical basis to assess AI model quality. Organizations use a range of metrics to measure every aspect of the AI model — from output, to speed, user experience and even ethics. This article covers 30+ metrics you can use to track AI progress.

This blog explores the process of AI model hosting, where trained models are deployed and made accessible via APIs for users and applications. It covers the complexities of running AI workloads in distributed environments, the different technology layers involved and key factors like performance, cost and security when choosing the best hosting option.

This month’s digest is our most packed so far. We’re opening pre-orders for NVIDIA Blackwell GPU-powered clusters, expanding to a new US data center in Q1 2025 and opening offices there. Both of our R&D teams, AI and hardware, shared their latest developments, and more.

In this hands-on tutorial, you’ll learn how to create a powerful code generation and review application that you can customize to your exact needs. We’ll use Nebius AI Studio and open-source models, making it both cost-effective and extensible.

Explore the importance of context windows in AI and LLMs. Learn how context window size affects model performance, tokenization and natural language processing.

In this guide, we’ll build an AI-powered financial planner using the Meta Llama 3.1 70B model via Nebius AI Studio and a full-stack Next.js app. This solution works seamlessly whether you’re using the Pages Router or the App Router, as much of the customization relies on setting up a custom Next.js server.

Among the many database options available, PostgreSQL stands out as a tool of choice for ML engineers. This article explores why and how you can use PostgreSQL to increase efficiency and speed in ML development.