Top 50 Ai Gpu Cloud in Europe

This company provides cloud-based GPU infrastructure for AI and machine learning, offering flexible access to computing power. Their liquid cooling solutions optimize GPU performance and efficiency, reducing operational costs for users.

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.

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.

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.

Verda Cloud provides a full-stack GPU cloud platform optimized for AI workloads, offering on-demand instances, instant clusters, and serverless containers. The platform delivers high-performance compute, storage, and networking with a developer-first experience at significantly lower costs than hyperscalers. Users gain immediate access to cutting-edge NVIDIA hardware for efficient model training, experimentation, and scalable inference.

AI Grid offers cost-effective GPU compute for AI model training and deployment, providing access to NVIDIA RTX pro 6000 GPUs at significantly reduced rates. The platform delivers dedicated server resources optimized for AI workloads, enabling startups and research institutions to accelerate development and lower operational expenditures.

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.

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.

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.

This company provides a unified, software-defined AI infrastructure platform for building and deploying machine learning models across any cloud or hardware. It abstracts the hardware layer, enabling instant deployment, seamless architecture switching, and high GPU utilization. The platform optimizes compute routing based on user-defined priorities like speed, cost, and location while minimizing data movement.

AiReplyit Inc has developed a patent-pending PCB layout design that transforms standard gaming GPUs into efficient processors for large language models, significantly lowering the cost of AI computing. This technology enables researchers and small companies to access high-performance AI capabilities without the need for expensive, specialized hardware.

Stelia provides a data mobility platform that facilitates seamless data transfer and accessibility across diverse AI infrastructures. This technology eliminates data silos and enhances data management, enabling organizations to optimize AI workflows and improve decision-making efficiency.

The startup offers a cloud platform that streamlines development processes by automating environment management and hosting, allowing developers to focus more on coding. This solution reduces infrastructure costs and minimizes the time spent on operational tasks, enhancing overall productivity.

Gcore provides cloud and edge computing solutions that enhance content delivery, hosting, and security for businesses. By optimizing data transfer and storage, Gcore addresses latency and security challenges faced by companies operating in a digital landscape.

SpiNNcloud provides ultra energy-efficient computing infrastructure specifically optimized for next-generation AI inference workloads. Their brain-inspired chip architecture leverages dynamic sparsity to achieve significantly higher energy efficiency compared to traditional GPUs. This infrastructure enables scalable, low-power AI processing necessary to address growing GenAI energy demands.

CodeDepot offers Git AI, a Git-native MLOps platform designed to streamline the AI development workflow. This platform enables users to build and deploy AI models across diverse cloud environments, including platform-less GPU clouds and on-premises infrastructure. The core value is providing developers with integrated version control directly within their machine learning operations for enhanced control and deployment flexibility.

This startup develops AI agents that automate tasks and optimize resource allocation within smart city infrastructure. Their technology enables cities to improve efficiency in areas like traffic management, energy consumption, and public safety through intelligent automation.

Golem Network is an open-source, decentralized platform connecting users globally to share and access computational power. Requestors utilize this distributed capacity for tasks like rendering and AI modeling, while Providers monetize their spare resources. The GLM token facilitates these transactions, creating a self-sustaining ecosystem for decentralized computing.

The startup offers a machine-learning community platform that facilitates collaboration on models, datasets, and applications, enabling users to create and discover machine-learning projects. By providing paid computing resources and enterprise systems, the platform enhances the efficiency of open-source development, allowing users to contribute to and advance the field of machine learning.

The startup offers an artificial intelligence platform that enables organizations to extract, prepare, and process data for machine learning workflows, facilitating the transition from experimentation to production. This platform provides a secure and scalable solution to enhance the efficiency and performance of AI projects, addressing the challenges of data management and deployment in AI development.

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.

evroc provides a modern, energy-efficient cloud infrastructure designed specifically to support AI workloads. This European cloud integrates infrastructure, software, and services to ensure data sovereignty and robust security for its users. The platform emphasizes sustainability through its data center operations, offering a cleaner alternative for compute needs.

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.

This company provides the Haystack open source framework and enterprise platform for building custom AI solutions powered by LLMs. They specialize in high-impact applications such as Retrieval Augmented Generation (RAG), AI Agents, and Intelligent Document Processing (IDP). Their technology enables organizations to deploy trusted, sovereign AI solutions with control over data, models, and workflows.

The startup offers a Python-centric feature store that enables data teams to efficiently build and manage feature, training, and inference pipelines at scale. This platform enhances the performance and availability of AI and machine learning applications across diverse data sources and environments, facilitating the development of data-driven products for business growth.

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.

This company provides cloud infrastructure specifically optimized for running large-scale AI applications. Their AI-focused IaaS cloud solutions enable businesses to efficiently scale and manage their AI workloads, offering an alternative to traditional cloud providers.

Virtuozzo provides a white‑label, full‑stack cloud platform that runs on a provider’s existing hardware and combines compute, software‑defined block/file/object storage and Kubernetes orchestration into a single management layer. The solution delivers near‑bare‑metal performance, automated zero‑downtime operations, tenant isolation and encryption, and exposes open APIs and a multi‑tenant billing engine for IaaS, PaaS or managed cloud services under the provider’s brand.

Cudos provides a decentralized cloud computing network that allows users to deploy virtual machines and write smart contracts using a globally distributed resource pool. This platform addresses the need for cost-effective, secure, and scalable infrastructure for decentralized applications by enabling permissionless access through digital wallets.

Xoda provides a decentralized AI platform integrating Blockchain, IPFS, and LLMs to enable secure research, analysis, and development. The platform supports AI model developers with tools for building and monetization, and application developers in creating new AI-powered solutions. Resource providers can contribute compute power to the ecosystem while users benefit from transparent and autonomous AI development.

Axelera AI develops AI processing units (AIPUs) and associated software like the Voyager SDK to accelerate AI inference workloads. Their hardware solutions, including Metis AIPUs on M.2 and PCIe cards, deliver high performance and power efficiency for edge computing applications. This technology enables customers to deploy complex deep neural networks for computer vision and analytics at a lower cost and power consumption than traditional GPU solutions.

Zerve AI offers an AI‑native data workspace that combines a multi‑language notebook with a contextual agent capable of generating, planning, and executing data pipelines from natural‑language prompts. The platform includes built‑in Git versioning, real‑time multi‑user collaboration, and one‑click deployment of notebooks as APIs, interactive apps, or scheduled jobs on managed or self‑hosted compute environments. It is designed for data scientists, analysts, and ML engineers who need reproducible, production‑ready workflows.

YOM operates the world's first decentralized cloud gaming network that utilizes idle gaming rigs to deliver on-demand, cross-platform gaming solutions at ten times the efficiency of traditional data centers. This approach significantly reduces operational costs for game studios while promoting sustainable computing by recycling consumer hardware.

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.

The startup develops a decentralized quantum computing platform utilizing a network of Graphic Processing Units (GPUs) to execute quantum algorithms with quantum entanglement and tunneling effects. This technology enables users to tackle complex real-world problems at scale, enhancing computational efficiency and problem-solving capabilities.

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.

Perian provides an AI platform designed for enterprise use within Europe. This platform facilitates the transition of ideas into production environments smoothly. It is built to be fully GDPR compliant and ready for adherence to the EU AI Act.

DeepSquare offers a decentralized high‑performance computing platform that lets users submit jobs via a simple YAML workflow, abstracting complex runtimes and scripts. The ecosystem leverages blockchain‑based scheduling to provide transparent, fair access to GPU, CPU and accelerator resources across a distributed network. Compute resources are paid for and rewarded with the DPS token on the Avalanche network, enabling sustainable and professional HPC for AI, rendering, and simulation workloads.

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%.

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.

Klepsydra Technologies provides patented edge AI software solutions optimized for high-performance, low-latency inference in demanding sectors like aerospace and robotics. Their acceleration technology achieves significant gains in throughput and power efficiency through two-dimensional parallelization and lock-free programming. The unified API ensures hardware independence, allowing clients to deploy optimized AI across diverse edge computing platforms.

Quynta develops advanced machine learning models for predictive analytics in the financial sector. The platform processes complex market data to generate actionable insights for investment strategies. This enables quantitative firms to optimize portfolio performance and manage risk exposure effectively.

gridscale provides a user-friendly platform for creating and managing private cloud infrastructures through intuitive drag-and-drop web interfaces, enabling businesses to deploy complex IT environments in minutes. The service addresses the challenges of scalability, security, and vendor lock-in by offering flexible, on-demand resources with European data protection compliance.

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 unified platform for data science and AI development, combining an integrated IDE with parallel processing, language interoperability, and automated cloud infrastructure. It streamlines workflows by decoupling compute and storage, enabling enterprise-scale collaboration, version control, and seamless deployment from exploration to production.

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.

dstack provides a unified control plane for GPU provisioning and orchestration across cloud, Kubernetes, and on-prem environments for ML teams. This platform streamlines development, training, and inference workflows while significantly reducing infrastructure costs. It offers an open stack supporting any hardware, open-source tools, and custom code for managing AI workloads.

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.

AMSIMCEL develops a GPU-powered Physical Verification framework for Integrated Circuits, significantly enhancing verification speed and scalability in chip design. This technology addresses the inefficiencies of traditional CPU-based solutions, delivering performance that is 20 times faster while maintaining accuracy comparable to foundry standards.

DimensionLab's Siml.ai platform accelerates engineering simulations using AI, reducing virtual prototyping from months to hours. It provides a web-based interface for training AI simulators and running complex CFD and physics-based analyses, making advanced simulation accessible and enabling faster design cycles.