Top 50 Ai Gpu Cloud in Europe

Provides a fully managed AI cloud platform powered by NVIDIA® H100 and H200 Tensor Core GPUs, offering scalable GPU clusters with InfiniBand networking for high-speed data processing. Enables efficient model training, fine-tuning, and inference with tools like MLflow, PostgreSQL, and Apache Spark, reducing the complexity and cost of deploying AI applications at scale.

Nscale provides a GPU cloud platform optimized for AI workloads, featuring on-demand compute and inference services, dedicated training clusters, and scalable GPU nodes. The platform addresses the high costs and inefficiencies associated with AI model training and deployment by offering a fully integrated infrastructure powered by renewable energy in Europe.

Genesis Cloud provides a GPU cloud platform built on NVIDIA's reference architecture, delivering up to 35 times more performance for AI and machine learning workloads at 80% lower costs compared to traditional cloud providers. The platform ensures high security and compliance with EU regulations, enabling enterprises to efficiently manage and scale their AI applications.

FluidStack provides on-demand access to thousands of NVIDIA A100 and H100 GPUs, enabling AI engineers to rapidly scale their training and inference workloads without long-term contracts. The platform offers fully managed GPU clusters with 24/7 support, significantly reducing operational overhead and accelerating model deployment.

DataCrunch provides on-demand access to high-performance GPU instances and custom-built clusters powered by NVIDIA H200 and H100 technology, enabling efficient model inference and training for machine learning applications. The platform utilizes 100% renewable energy, offering a scalable solution that reduces the infrastructure burden for businesses deploying AI models.

NexGen Cloud provides sustainable Infrastructure as a Service (IaaS) with a focus on high-performance computing (HPC) and GPU infrastructure, utilizing its Hyperstack platform for on-demand GPU as a Service (GPUaaS). The company enables businesses to efficiently integrate AI capabilities into their operations while ensuring data privacy and compliance through its European and North American data centers.

Ori provides on-demand access to top-tier GPUs and serverless Kubernetes for training and deploying machine learning models at scale. The platform offers cost-optimized solutions that allow users to pay only for the resources they utilize, addressing the need for flexible and efficient AI infrastructure.

PERIAN provides a serverless Sky Computing Platform that offers unified, on-demand access to a wide range of GPU resources across multiple cloud providers, enabling efficient management and deployment of GPU workloads. The platform's cost optimization features ensure users consistently access the most competitive pricing, resulting in potential savings of up to 87% on cloud computing expenses.

InstaDeep develops AI-powered decision-making systems utilizing GPU-accelerated computing, deep learning, and reinforcement learning to tackle complex challenges in industries such as logistics, energy, and biology. Their technology enhances operational efficiency and precision, enabling enterprises to make data-driven decisions in an increasingly AI-centric landscape.

RaiderChip designs semiconductor hardware accelerators that enhance AI performance by addressing memory bandwidth limitations. Their solutions enable efficient AI inference for both edge and cloud applications, allowing users to run complex large language models locally with full privacy and without ongoing subscriptions.

Avesha provides a technology platform that enables efficient management and orchestration of application workloads across cloud, multi-cloud, and edge environments using predictive algorithms and automated scaling. The platform addresses high Kubernetes costs and inefficient GPU utilization by optimizing resource allocation and performance in real-time.

FlexAI provides a universal AI compute platform that enables developers to run AI workloads across diverse hardware architectures without code modifications. This approach maximizes resource utilization and energy efficiency, reducing operational complexity and minimizing failures in AI product development.

Leafcloud offers sustainable cloud infrastructure by repurposing server waste heat to warm urban buildings, reducing environmental impact and operational costs. They provide core cloud services like VMs and GPUs on a distributed network of urban sites, built on open-source technology for data sovereignty and flexibility.

Mistral AI provides open-weight generative AI models that developers and businesses can customize and deploy in various environments, including on-premise and cloud platforms. Their technology enhances AI application development by offering high-performance models with validated reasoning capabilities, ensuring independence from specific cloud providers.

iGenius utilizes one of the world's largest AI supercomputers, powered by NVIDIA Grace Blackwell Superchips, to deliver augmented analytics tailored for regulated industries. Their solutions enhance data security and accuracy, enabling organizations to derive actionable insights from complex business data while meeting stringent regulatory requirements.

This startup provides sustainable data center infrastructure featuring ultra-high-density and liquid cooling capabilities with heat reuse. Their solutions enable hyperscalers and cloud providers to efficiently scale AI-optimized computing environments while meeting ESG objectives.

NeuralAgent develops a decentralized AI-Operating System called Neural Cloud, which enables high-bandwidth connectivity and autonomous learning across space, airborne, and ground transport systems. This technology addresses the challenges of dynamic routing and data transfer for connected intelligence, significantly enhancing operational efficiency and reducing costs in telecommunications, defense, and mobility sectors.

ConfidentialMind provides a generative AI software infrastructure that enables developers to build and deploy complex AI applications in on-premises and private cloud environments, ensuring data sovereignty and security. The platform simplifies the management of AI models, databases, and application lifecycles, allowing organizations to leverage their proprietary data without the need for extensive custom engineering.

The startup has developed a protocol tailored for the computational demands of global deep learning models in machine learning. This technology enhances processing efficiency and scalability, addressing the challenges of resource-intensive AI applications.

DePIN is a decentralized compute network that utilizes the processing power of millions of smartphones, desktops, and data centers to provide low-cost AI processing. This infrastructure enables companies to scale their AI applications efficiently without incurring high computational costs.

Runware provides an ultra-fast API for generative media, utilizing custom hardware and renewable energy to deliver image generation at sub-second speeds and costs as low as $0.0006 per image. The platform eliminates the need for specialized infrastructure or machine learning expertise, enabling users to access over 180,000 open-source models and seamlessly integrate AI content generation into their applications.

Axelera AI manufactures AI acceleration hardware, specifically the Metis AI Processing Unit (AIPU), designed for efficient edge computing with up to 214 TOPS performance and 15 TOPS per watt. The technology addresses the need for cost-effective and energy-efficient solutions in generative AI and computer vision applications across various industries, including retail and security.

Sync Computing develops Gradient, a machine learning-based optimization processing unit that automates compute resource management for data infrastructure on cloud platforms. By reducing Databricks costs by up to 50% and saving engineering hours, Gradient ensures organizations meet their runtime service level agreements efficiently.

deepset provides an open-source framework, Haystack, and a cloud platform for enterprises to develop and deploy custom applications using large language models (LLMs). This technology enables organizations to efficiently prototype, test, and launch AI-driven solutions that enhance data processing and improve decision-making across various business functions.

SKY ENGINE AI provides a Synthetic Data Cloud that generates multimodal synthetic data for training deep learning models in computer vision, significantly reducing the need for real-world image acquisition. This technology enhances model accuracy by up to 4150% and accelerates AI development cycles by up to 3340 times, addressing the challenges of data scarcity and high costs in various industries such as automotive, healthcare, and robotics.

Gensyn is a machine learning compute protocol that connects distributed resources to facilitate the training of deep learning models. This approach addresses the need for open, permissionless, and neutral frameworks that enable efficient scaling and collaboration in machine intelligence development.

TitanML provides an enterprise-grade LLM cluster for high-performance language model inference, enabling organizations to deploy AI applications securely within their own infrastructure. This solution addresses the need for data privacy and control while optimizing operational costs and performance through advanced inference techniques.

Qoro develops network software that integrates quantum and classical computing systems, enabling efficient resource sharing across diverse hardware, including GPU clusters and quantum computers. The platform automates quantum program development, eliminating hardware-specific complexities for users while providing a robust network stack for hardware providers.

NetMind offers a unified platform for accessing and deploying diverse AI models, including LLMs and multimodal capabilities, through standard APIs and the Model Context Protocol. The service simplifies AI infrastructure by providing on-demand GPU cluster rentals and managed inference endpoints, enabling developers to integrate AI without managing complex deployments.

Provides a cloud-based platform for building, deploying, and scaling AI agents using Python, integrating frameworks like LangChain and Haystack. It streamlines the development process by offering pre-built templates, API integration, and serverless infrastructure, enabling developers to create secure, production-ready AI solutions with no fixed fees.

The startup develops decentralized artificial intelligence networks that enable developers to create scalable AI infrastructure with improved performance compared to centralized systems. This technology allows companies to enhance their AI capabilities and reach while reducing reliance on traditional network architectures.

Graphcore designs and manufactures Intelligence Processing Units (IPUs) and the Poplar software stack to accelerate machine learning workloads. Their technology enables faster training and inference for complex AI models across various industries. IPUs are optimized for the parallel processing demands of deep learning, offering a distinct advantage for AI innovation.

UbiOps provides a unified MLOps platform that enables the deployment and management of AI workloads across local, hybrid, and multi-cloud environments. By streamlining AI operations with built-in features like version control and automatic resource scaling, UbiOps reduces infrastructure overhead and development costs by up to 80%.

Xelera Suite accelerates data center and cloud workloads by utilizing DPU and SmartNIC technologies to enhance network throughput and machine learning model performance. This software reduces compute latency and energy consumption, enabling efficient processing for applications in cybersecurity, telecom, and edge computing.

Saint offers Halo, an AI‑native creative platform hosted on a private EU cloud with Nvidia GPU acceleration, that ingests a brand’s first‑party data and guidelines to generate data‑driven “lenses” guiding market research, audience segmentation, multi‑format asset creation and performance analytics. The platform includes a Copy Engine for automated copywriting, localization and testing, and can be accessed as a managed service or self‑service portal, ensuring encrypted, isolated data compliance with EU privacy regulations while scaling creative output without additional headcount.

dstack is an open-source orchestration engine that simplifies the management of AI workloads across cloud and on-premises environments, supporting various hardware accelerators like NVIDIA and TPU. dstack Sky provides a global marketplace for affordable GPUs, enabling AI engineers to access cost-effective computing resources without the high premiums typically associated with major cloud providers.

GENXT.AI provides confidential AI solutions that allow enterprises to utilize large language models (LLMs) without exposing sensitive data, ensuring that all business and private information remains encrypted and inaccessible to third parties. Their technology enables secure model deployment, fine-tuning, and inference within isolated cloud environments, mitigating the risks of data leakage and ensuring compliance with data protection regulations.

Lumai develops a 3D optical processor that significantly enhances AI performance in data centers while achieving a 90% reduction in power consumption compared to traditional silicon-based solutions. This technology addresses the escalating demand for AI processing power by providing a scalable, energy-efficient alternative that lowers both capital and operational costs.

Develops cloud management software optimized for ARM, RISC-V, and Intel architectures to improve data center resource allocation and reduce energy consumption. By integrating AI-powered analytics, smart scheduling, and automated workload management, it enables data centers to lower operational costs and minimize their carbon footprint. The platform supports migration to energy-efficient processors and provides tools for real-time performance monitoring and optimization.

This company provides a cloud platform with data analytics, AI automation, and infrastructure management tools to help businesses modernize their operations. Their platform enables businesses to accelerate digital transformation, optimize processes, and improve agility.

Doubleword AI provides an inference platform that lets enterprises run large language models securely across on‑premise, private‑cloud, and public‑cloud environments. Its Batch Inference service delivers high‑throughput, cost‑optimized token processing with 1‑hour and 24‑hour SLAs, while the Control Layer adds centralized authentication, role‑based access, usage metering, and audit‑ready logging. The platform auto‑generates OpenAI‑compatible endpoints, uses GPU‑aware autoscaling and infrastructure‑as‑code for reliable, self‑healing deployments, enabling AI/ML teams to serve models without building custom infrastructure.

Celestical provides a GDPR-compliant cloud computing platform optimized for AI LLM workloads and general applications. It offers high-performance infrastructure with predictable costs and automated server operations for efficient development, deployment, and scaling.

Pointly is a cloud-based platform that utilizes AI techniques for the automatic and manual classification of large 3D point clouds, enabling efficient data vectorization and precise 3D modeling. This technology addresses the challenge of slow and inaccurate point cloud analysis, significantly reducing processing time and improving classification accuracy for various applications.

Zymtrace provides a continuous profiling solution that delivers deep insights into CPU and GPU performance for general-purpose and accelerated computing workloads. By identifying inefficiencies in applications, models, and inference processes, Zymtrace enables users to optimize resource utilization and improve overall computational efficiency.

VALDI offers on-demand GPU computing power and scalable storage solutions for applications in Generative AI, Machine Learning, and Drug Discovery, utilizing a pay-as-you-go model with no contracts or hidden fees. By providing access to high-performance GPUs like the NVIDIA H100 and A100 at competitive rates, VALDI addresses the need for affordable and flexible computing resources in data-intensive industries.

The startup develops decentralized artificial intelligence software that utilizes cryptography and electronic money to enable individuals and organizations to operate their own model training clusters. This platform allows users to contribute to and benefit from AI model development without dependence on centralized systems, promoting broader access to advanced AI capabilities.

Hyground provides an AI-powered platform for automated, real-time incident diagnosis and resolution within Kubernetes environments. It operates entirely within your virtual private cloud, ensuring data residency and privacy while accelerating root cause analysis and incident resolution.

Moterra offers a private‑cloud generative AI platform that runs within a customer’s own cloud environment, enabling retrieval‑augmented generation over internal repositories such as SharePoint, Google Drive, and relational databases. The solution provides task‑specific assistants for knowledge search, content drafting, data analysis, and document comparison, all with role‑based access, audit logs, and compliance certifications (ISO 27001, GDPR, SOC 2).

Asperitas offers immersion cooling technology that enhances CPU and GPU performance while reducing capital and operational expenses for data centers. This solution enables high-density computing with a 45% lower cost and an 80% smaller physical footprint compared to traditional air cooling methods, while reusing 99% of energy.

Enot offers neural network compression and acceleration tools to optimize AI model performance for faster inference and lower computational overhead. Their platform reduces model complexity and memory footprint, enabling efficient AI deployment on edge devices and in the cloud.