详细内容
Introducing Nebius Token Factory: production inference at scale
Flexible architecture
Scale AI seamlessly from a single GPU to pre-optimized clusters with thousands of NVIDIA GPUs, supporting both training and inference at any size.
Tested performance
Engineered for demanding AI workloads, Nebius integrates NVIDIA GPU accelerators with pre-configured drivers, high-performance InfiniBand, and Kubernetes or Slurm orchestration for peak efficiency.
Long-term value
By optimizing every layer of the stack, Nebius offers unparalleled efficiency, delivering substantial customer value over competitors.
Nebius Robotics & Physical AI Awards
Nebius Robotics & Physical AI Awards celebrate emerging startups and scale-ups that use AI to shape the future of the industry.
Our mission is to showcase transformative technology, foster collaboration between founders, industry leaders and researchers and power the next generation of breakthroughs in AI.
The finalists are selected!
AI Cloud + Token Factory for every AI need
We provide every essential resource for your AI journey
Latest NVIDIA® GPUs
Choose the GPU that suits you best: NVIDIA GB200 NVL72, HGX B200, H200, H100 or L40S. Benefit from an InfiniBand network with up to 3.2Tbit/s per host.
Thousands of GPUs in one cluster
Orchestrate and scale your environment by using our Managed Kubernetes® or Slurm-based clusters and fast storage.
Fully managed services
Benefit from reliable deployment of MLflow, PostgreSQL and Apache Spark with zero effort on maintenance.
Cloud-native experience
Manage your infrastructure as code by using Terraform, API and CLI, or try our intuitive and user-friendly console.
Ready-to-go solutions
Access everything you need in just a few clicks: third-party solutions, Terraform recipes, detailed tutorials.
Architects and expert support
Receive 24/7 expert support and dedicated assistance from our solution architects for multi-node cases, all free of charge.
We master building AI-optimized sustainable data centers
We filmed this video 60 kilometers from Helsinki, the home of the first Nebius data center. This is where we built ISEG, the #19 most powerful supercomputer in the world. And there’s more: we also constructed a supercluster of thousands of GPUs installed into servers and racks of our own design.
Competitive pricing for NVIDIA GPUs
Access improved cost savings on NVIDIA GPUs with a commitment of hundreds of units for at least 3 months.
NVIDIA GB200 NVL72
Pre-order
Be among the first to get access to NVIDIA GB200 NVL72, the most advanced NVIDIA accelerators on the market.
NVIDIA B200 GPU
$3.00/ per hour
Intel Emerald Rapids
1x or 8x B200 GPU
180GB SXM
16x or 128x vCPU
224 or 1792 GB DDR5
3.2 Tbit/s InfiniBand
NVIDIA H200 GPU
$2.30/ per hour
Intel Sapphire Rapids
1x or 8x H200 GPU
141GB SXM
16x or 128x vCPU
200 or 1600 GB DDR5
3.2 Tbit/s InfiniBand
NVIDIA H100 GPU
$2.00/ per hour
Intel Sapphire Rapids
1x or 8x H100 GPU
80GB SXM
16x or 128x vCPU
200 or 1600 GB DDR5
3.2 Tbit/s InfiniBand
Tested with GenAI workloads
CRISPR-GPT: AI gene-editing expert designed at Stanford
CRISPR-GPT is an LLM-powered agent system developed by scientists from Stanford, Princeton and Google DeepMind, which automates gene-editing experiments, from CRISPR system selection to decision making when designing gene-editing RNA to 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 their first attempt. An undergraduate student can be onboarded in one day, and even expert users can work faster by using the AI agents to help run analysis, check designs and troubleshoot experiments.
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Training
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Life sciences
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Research
100%
success rates for novice researchers
Training time reduced from weeks-to-months down to
1 day
Agentic automation
of design and analysis that integrates gene-editing expert knowledge
Accelerating AI innovation in retail
Shopify builds infrastructure to make millions of merchants’ products machine-readable, enabling innovative ways to discover and interact with products beyond improved search and recommendations.
Goal: Lead in AI-driven technology, offering features like enhanced product search and streamlined checkout processes to improve merchant outcomes.
Solution: Nebius provides large-scale GPU clusters for AI model development and experiments.
Result: Shopify’s ML engineers have the scalable compute resources to innovate quickly.
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Inference
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E-com
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Large-scale
10M
product updates processed daily
40M
LLM calls daily, supported by inference infrastructure
16B
tokens inferred per day
vLLM: Advancing open-source LLM inference
vLLM is an open-source framework under the Linux Foundation, designed to optimize LLM inference at scale. It enables organizations to deploy and serve large language models with greater efficiency, reducing infrastructure costs and enhancing performance.
Goal: To develop and continuously optimize vLLM framework for efficient LLM inference, enabling organizations to serve large language models at lower costs while ensuring scalability and performance optimization.
Solution: The Nebius team provided vLLM with reliable access to cutting-edge compute accelerators and compute clusters for large-scale inference experiments.
Result: With Nebius, vLLM has successfully optimized inference performance for transformer-based models, including DeepSeek R1. The project has achieved high-throughput inference, seamless scalability, and integration of advanced features like multi-latent attention and multi-token prediction.
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Inference
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Open-source
Zero
hardware-related issues
Consistently
accurate hardware performance metrics
Compute clusters to run
DeepSeek R1
Enhancing AI-powered search
Brave Software, with over 80 million users, develops a fast, privacy-focused browser and Brave Search, an independent search engine. Its AI-powered feature, Answer with AI, provides real-time, privacy-centric summaries for user queries.
Goal: To generate AI-driven search responses with modern compute infrastructure.
Solution: Brave uses Terraform for provisioning and HAProxy for load balancing, ensuring efficient AI inference, real-time response generation and seamless traffic scaling.
Result: With Nebius, Brave runs 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.
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Inference
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Web search
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AI summaries
10–70B
LLM parameters
1.3B
search queries per month
11M+
AI-generated answers daily
Cost-efficient AI deployment platform
The CentML Platform powers open-source model deployment with automated compute optimizations and flexible configurations. CentML delivers state-of-the art inference at reduced costs, without vendor lock-in.
Goal: Give customers access to a highly performant, cost-optimized full stack solution for AI deployment.
Solution: CentML uses Nebius compute alongside ML techniques to optimize their inference platform, delivering flexible scaling, streamlined deployments and enhanced hardware utilization for AI models.
Result: Significant cost savings, improved reliability and scalability, and enhanced EU-based compute capabilities. Customers can reduce infrastructure complexity and securely deploy open-source LLMs.
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Inference
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Open-source
x5
lower costs compared to other major providers
Enhanced
compliance with EU compute requirements
1 week
to get cluster online
Stable diffusion inference
TheStage AI builds inference simulators and DNN optimization tools for a wide range of hardware, significantly reducing GPU costs.
Goal: To enhance the capabilities of TheStage AI platform with a focus on stable diffusion architecture.
Solution: To run tests on TheStage AI acceleration framework, particularly on the computationally intensive UNet component, using the open-source Stable Diffusion v1-5 model by RunwayML.
Result: Two acceleration methods — quantization and structured sparsification — were implemented using NVIDIA H100 Tensor Core GPUs for efficient INT8 and sparse computation. The project resulted in a significant reduction in the number of GPUs needed for inference.
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H100
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Inference
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Stable diffusion
4x leap
in speed over the early version of the framework running on A100
~500 ms
to process one image during inference
1B parameters
of the model
Training gen AI foundational model
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.
Goal: To train the first generative AI model for designers from scratch.
Solution: To utilize all the key parts of Nebius AI and implement PyTorch + Kubeflow, with NCCL used for the hardware setup.
Result: Thanks to the contributions from the Nebius support and architect teams, Recraft overcame hardware configuration challenges and achieved remarkable system stability.
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GenAI
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Training
20B
model parameters
Comparable
to DALL·E 3 with 49% preference on PartiPrompts benchmark
54%
preference over Midjourney v6 on the same benchmark
Streamlining music creation through AI
Wubble is a cutting-edge AI platform designed to empower businesses to generate high-quality, royalty-free music instantly, streamlining creative processes and unlocking limitless possibilities for marketing, advertising, podcasts, games, stores and more.
Goal: To optimize AI operations and model deployment for scalable, efficient and low-latency music generation.
Solution: Leveraging Nebius’ infrastructure and Kubernetes, Wubble built a scalable system for managing workloads and deployments.
Result: The company achieved high-capacity inference, QLoRA adaptation and faster audio analysis pipelines. These advancements reduced the time to first token and ensured reliable performance, while integration with GCP enabled robust scalability and efficient resource utilization.
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Media
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Inference
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LoRA
3B+
model parameters
100+ genres
the model is conversant in
1.8 seconds
Reduced time to first token generation
Quantum Chemistry for drug and material discovery
Simulacra AI is transforming the quantum chemistry field by automatically generating high-precision datasets for molecular dynamics models at scale.
Goal: Build a scalable foundational wave-function model for molecular systems that can generate high-accuracy datasets for pipelines of drug and material discovery.
Solution: Simulacra AI used Nebius infrastructure to overcome scalability and efficiency challenges.
Result: Simulacra AI delivers next-generation molecular data, enabling any company to refine in silico pipelines without relying on broad internal infrastructure to train models.
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Training
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Research
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Quantum tech
100M+
model parameters
90% faster
Thanks to Nebius infrastructure, our largest models take 10–20 minutes to compile for pre-training, compared to over 2 hours previously
H100 + H200
NVIDIA Tensor core GPU fleet
Advancing molecular generation
Quantori is the end-to-end data, technology and digital services partner of choice for leading biopharma and healthcare organizations worldwide.
Goal: To develop an AI framework that generates molecules with precise 3D shapes, enhancing drug discovery and material design.
Solution: Quantori employs a pipeline based on Equivariant Diffusion Model and Structure Seer model trained on 1.6M molecules from the ChEMBL database. The pipeline generates molecular structures using shape descriptors.
Result: After 1,500 training epochs, the model successfully generated chemically sound molecules that closely resemble real molecules in shape. The approach enables rapid molecular ideation, predicting valid 3D conformations with optimized properties.
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Training
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Drug discovery
1.6M
molecules from ChEMBL — dataset size
1,500 epochs
Training duration
High similarity
to reference geometries
In-house AI R&D
It wouldn’t be possible for us to build a truly AI‑centric cloud without advancing in the field ourselves — so we have a secret ingredient. Our in-house AI R&D team is dogfooding our platform, to help us adjust it to the real needs of ML practitioners.
Reference Platform NVIDIA Cloud Partner
Nebius takes a significant leap forward, elevating its NVIDIA Partner Network preferred status to Reference Platform Cloud Partner, solidifying its position as a trusted leader in cloud innovation. The Reference Platform NCP is designated for select partners who operate large clusters built in coordination with NVIDIA, and adhere to a tested and optimized reference architecture.
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