AI Infrastructure & GPU Cloud - European AI Compute

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AI Infrastructure & GPU Cloud - European AI Compute

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Nebius is a AI infrastructure and GPU cloud platform designed for AI explorers, providing comprehensive cloud services for training and inference at scale. The platform has been validated by multiple high-profile AI projects across diverse domains. CRISPR-GPT: AI Gene-Editing Expert (Stanford/DeepMind): CRISPR-GPT is an LLM-powered agent system developed by scientists from Stanford, Princeton and Google DeepMind to automate gene editing experiments, from CRISPR system selection to sgRNA design and data analysis. Goal: Transform gene editing from a months-long process into automated workflows accessible to any scientist. Solution: Enabling rapid model screening and fine-tuning via Nebius. Result: Junior researchers with no gene editing experience now achieve 80-90% efficiency on first attempt. Undergraduate students are onboarded in a day, and experts work faster by using AI agents to help run analysis, check designs and troubleshoot experiments. vLLM: Advancing Open-Source LLM Inference: vLLM is an open-source framework under the Linux Foundation, designed to optimize LLM inference at scale. With Nebius, vLLM has successfully optimized inference performance for transformer-based models, including DeepSeek R1. The project achieved high-throughput inference, seamless scalability, and integration of advanced features like multi-latent attention and multi-token prediction. Brave Software: AI-Powered Search: Brave Software, with over 80 million users, uses Nebius to run large AI models with nearly 100% compute utilization, delivering real-time AI summaries for over 11 million queries daily. The scalable infra allows Brave Search to provide faster, more relevant answers while maintaining strict privacy standards. Brave runs 10–70B LLM parameters, processes 1.3B search queries per month, and generates 11M+ AI-generated answers daily. CentML: Cost-Efficient AI Deployment: The CentML Platform powers open-source model deployment with automated compute optimizations. Using Nebius compute alongside ML techniques, CentML delivers x5 lower costs compared to other major providers, enhanced compliance with EU compute requirements, and can get a cluster online in just 1 week. TheStage AI: Stable Diffusion Inference: TheStage AI builds inference simulators and DNN optimization tools for a wide range of hardware, significantly reducing GPU costs. Using NVIDIA H100 Tensor Core GPUs for efficient INT8 and sparse computation, the project achieved a 4x leap in speed over the early version of the framework running on A100, with ~500ms to process one image during inference. Recraft: Training Generative AI for Designers: Recraft is an AI design tool that lets users create and edit digital illustrations, vector art, icons and 3D graphics in a uniform brand style. Using all key parts of Nebius AI with PyTorch + Kubeflow, Recraft trained a 20B parameter model that is comparable to DALL·E 3 with 49% preference on PartiPrompts benchmark and 54% preference over Midjourney v6 on the same benchmark. Wubble: AI Music Generation: Wubble is a cutting-edge AI platform designed to empower businesses to generate high-quality, royalty-free music instantly. Leveraging Nebius' infrastructure and Kubernetes, Wubble achieved high-capacity inference, QLoRA adaptation and faster audio analysis pipelines, reducing time to first token generation to 1.8 seconds, with a 3B+ parameter model conversant in 100+ genres. Simulacra AI: Quantum Chemistry for Drug Discovery: Simulacra AI is transforming the quantum chemistry field by automatically generating high-precision datasets for molecular dynamics models at scale. Using Nebius infrastructure, Simulacra AI delivers next-generation molecular data, enabling any company to refine in silico pipelines without relying on broad internal infrastructure. Their largest models take 10–20 minutes to compile for pre-training, compared to over 2 hours previously, using 100M+ model parameters on NVIDIA H100 + H200 Tensor core GPU fleet.