Nebius launches AI Cloud 3.5 with serverless AI compute

2026-04-02 · Source: Tech Monitor · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Cloud Computing & IT Infrastructure · Depth: Intermediate, quick

Summary

Dutch AI cloud company Nebius has released version 3.5 of its AI Cloud platform, introducing several key enhancements now active on its global cloud infrastructure. The update adds serverless AI computing, designed to simplify operations and accelerate development for AI applications by automating infrastructure management. Nebius also integrated the NVIDIA RTX PRO 6000 Blackwell Server Edition GPU, making it available for intensive workloads like AI inference, robotics, and drug discovery. A new Data Transfer Service streamlines data movement between external S3-compatible storage and Nebius cloud regions. Further platform improvements include enhanced Managed Soperator flexibility, better observability in Managed Kubernetes, and a redesigned AI application marketplace. User administration capabilities have been expanded with granular role-based permissions, and new public APIs allow for more efficient billing data export. The serverless service is currently in public preview.

Key takeaway

For MLOps Engineers or CTOs evaluating cloud AI platforms, Nebius AI Cloud 3.5's serverless AI computing and NVIDIA RTX PRO 6000 GPU integration offer significant operational efficiencies and performance boosts. You should explore the public preview of the serverless service to reduce infrastructure management overhead and accelerate your AI model development and deployment cycles, especially for compute-intensive applications.

Key insights

Nebius's AI Cloud 3.5 simplifies AI development with serverless computing and enhanced infrastructure.

Principles

• Automate infrastructure for faster AI development.
• Provide specialized hardware for demanding AI tasks.

Method

The platform automates infrastructure setup and runtime processes for serverless AI, reducing manual overhead for development teams to experiment, train, and deploy models.

In practice

• Utilize serverless AI for rapid prototyping.
• Deploy NVIDIA RTX PRO 6000 for high-demand AI.
• Integrate S3-compatible storage with Data Transfer Service.

Topics

• AI Cloud 3.5
• Serverless AI Computing
• NVIDIA RTX PRO 6000 Blackwell
• Data Transfer Service
• Managed Soperator

Best for: CTO, VP of Engineering/Data, MLOps Engineer, AI Engineer, AI Architect, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by Tech Monitor.