Top 5+ GPU Cloud Providers in Russia

Best GPU Cloud Providers In Russia – Deep Analysis

In an era where Artificial Intelligence (AI), Machine Learning (ML), and High-Performance Computing (HPC) are not merely technological pursuits but fundamental drivers of national progress, the Russian Federation is strategically cultivating its indigenous capabilities within these transformative domains. The insatiable appetite for raw computational power, particularly the specialized processing prowess of Graphics Processing Units (GPUs), has become a defining characteristic of this technological ascent. This demand stems from the imperative to architect and train increasingly sophisticated AI models, sift through petabytes of complex data, and execute intricate simulations across scientific and industrial frontiers.

Responding to this clarion call, Russia’s GPU cloud ecosystem has blossomed, presenting a sophisticated tapestry woven from home-grown public cloud behemoths, telecom-backed digital platforms, and highly specialized AI service ateliers. These domestic champions collectively offer a compelling spectrum of GPU-accelerated solutions. This ranges from direct, unmediated access to bare-metal NVIDIA A100 clusters, delivering uncompromising performance, to agile, virtualized environments powered by versatile T4-class VMs. Crucially, this landscape operates under the umbrella of national data sovereignty, ensuring that sensitive information remains within Russia’s digital borders and adheres to stringent local regulatory frameworks such as the Federal Law 152-FZ on Personal Data.

This exhaustive exploration navigates the premier GPU cloud providers within Russia for the year 2025, meticulously detailing their arsenal of GPU options, elucidating their unique operational strengths and value propositions, and illustrating how they can serve as powerful catalysts for your most ambitious AI, ML, and HPC initiatives within the uniquely Russian digital milieu (GPU облако Россия, аренда GPU сервера в России).

Table of Contents:

1. Dataoorts GPU Cloud
2. Yandex Cloud
3. Selectel
4. MTS Web Services
5. VK Cloud
6. SberCloud
7. Rostelecom

Vanguard GPU Cloud Architects in the Russian Federation (2025)

1. Dataoorts GPU Cloud: Redefining AI-First Performance

Dataoorts is the first GPU cloud platform born in the India, purpose-built to power AI, ML, and Deep Learning workloads with uncompromising, bare-metal-like performance. Deployed on Kubernetes clusters, it comes pre-configured with cutting-edge NVIDIA H100 (80GB) and A100 (80GB) GPUs—ready to accelerate the future of AI.

GPU Options & On-Demand Pricing

Experience unmatched performance with industry-leading NVIDIA GPUs:

• NVIDIA H100 (80GB) – $2.28/hour
• NVIDIA A100 (80GB) – $1.62/hour
• NVIDIA RTX A6000 – $0.60/hour
• NVIDIA RTX A4000 – $0.18/hour

Cost-Efficient by Design

Powered by a patented Dynamic Allocation Engine, Dataoorts automatically shifts idle GPU capacity into spot-like pools, enabling:

• Up to 70% reduction in TCO for bursty, research-driven AI tasks
• Minute-level billing for maximum cost precision
• 6-month reserved plans offering up to 45% in savings—ideal for long-term AI development cycles

Flexible Free Tier & Bundles

While exact free tier details may vary, users benefit from:

• Immediate access to cost-saving features
• Transparent, pay-as-you-go pricing
• Highly discounted bundle options from the start

Serverless AI APIs for LLMs & OSS AI Models: Dataoorts also offers one of the most affordable and scalable API services for deploying top open-source AI models and LLMs—perfect for developers and startups focused on production-ready AI.

Why Choose Dataoorts?

• GPU Lite VMs: Cost-effective, versatile Lite VMs optimized for smaller-scale AI tasks
• 24/7 Dedicated Support: Reserved cluster users get round-the-clock expert assistance
• Container & VM Support: Seamlessly deploy across multiple OS images with both containers and Lite VMs
• Low Latency Edge Inference: Ultra-fast response times for real-time AI applications
• Multilingual AI Helpdesk: Localized support tailored to India’s diverse AI community

Built For:

• AI Developers andAI Startups needing powerful infrastructure on a friendly budget
• Research Institutions running complex training and inference pipelines
• Enterprises demanding consistent, high-performance compute for critical AI workloads
• Ideal for AI model training, fine-tuning, and deployment at scale

Dataoorts is more than just a GPU cloud—it’s the AI-native cloud frontier for upcoming AI waves, engineered for performance, flexibility, and cost-efficiency.

2. Yandex Cloud: A Symphony of Scalable GPU Acceleration and Integrated AI Prowess

• GPU Capabilities: Yandex Cloud positions itself as a formidable force in the Russian cloud arena, offering a versatile suite of attachable NVIDIA GPUs. This spectrum of computational engines ranges from the workhorse NVIDIA T4 and the robust V100 up to the powerhouse A100 cards, all available on an on-demand basis to align with fluctuating project requirements. This diverse offering ensures that workloads, from nimble inference tasks to demanding, protracted model training campaigns, find their optimal hardware match.
• Economic Framework: Fiscal flexibility is a key tenet, manifested through per-second billing that allows for meticulous cost tracking, complemented by sustained-use discounts designed to automatically optimize the economic outlay for protracted machine learning endeavors.
• Complimentary Access: Typically, Yandex Cloud extends an initial grant or trial credits to new patrons, facilitating exploration of its comprehensive platform, with these benefits being applicable towards GPU instance utilization. Precise terms are best confirmed via their official portal.
• Distinctive Attributes & Ecosystem: Beyond raw hardware, Yandex Cloud distinguishes itself through robust DevOps and MLOps integrations. A pivotal element is their Terraform provider, which capably supports the orchestration of GPU clusters underpinned by RDMA-backed networking. This is a critical feature for minimizing latency and maximizing throughput in distributed training paradigms, allowing multiple instances to work in concert with exceptional efficiency. This hardware prowess is seamlessly interwoven with Yandex’s broader AI ecosystem, notably the DataSphere collaborative ML development studio and the Managed Spark service. This holistic integration empowers data science teams to navigate the entire lifecycle—from prototyping and training to deployment—within a cohesive, unified console, proving particularly advantageous for Python-centric data science stacks.
• Optimal Use Cases: Yandex Cloud is tailor-made for data science collectives, AI development pioneers, and discerning enterprises across Russia that demand a highly scalable, deeply integrated cloud platform. It’s for those who require a broad selection of NVIDIA’s finest GPUs, appreciate granular pricing models, depend on cutting-edge distributed training infrastructure, and seek to leverage a rich suite of managed AI and ML services.

3. Selectel: Mastering Flexible GPU Server Provisioning and Bare-Metal Supremacy

• GPU Capabilities: Selectel carves a distinct niche by specializing in turnkey GPU server provisioning, empowering users with the ability to effortlessly incorporate NVIDIA A100, A30, or even potent consumer-class GPUs (such as the RTX series) into any cloud or dedicated bare-metal instance. This is facilitated through their intuitive Control Panel, offering unparalleled adaptability in hardware configuration.
• Economic Framework: Demonstrating a commitment to accessible power, Selectel has recently enacted substantial price reductions on its A100 and A30 GPU models, in some cases by as much as 44%. This move significantly bolsters their cost-competitiveness. Furthermore, they champion Multi-Instance GPU (MIG) technology, a sophisticated feature that allows high-end A100/A30 GPUs to be logically partitioned into multiple smaller, fully isolated GPU instances. This facilitates fine-grained hardware sharing, leading to considerable cost efficiencies, particularly for diverse and variable inference workloads.
• Complimentary Access: While a perpetual free tier dedicated to GPU resources is not standard, Selectel frequently introduces promotional offers or trial periods for its diverse service portfolio. Their core value proposition centers on providing highly competitive pricing structures for leased dedicated or virtualized server solutions.
• Distinctive Attributes & Ecosystem: Selectel places a premium on operational simplicity and accelerated deployment timelines. A testament to this is their provision of ready-to-deploy Ubuntu and CentOS images, meticulously pre-configured with the requisite CUDA and cuDNN drivers. This foresight allows users to instantiate and boot a fully GPU-accelerated virtual machine within a matter of minutes. The fusion of unadulterated bare-metal performance with the inherent flexibility of cloud architecture constitutes a primary attraction of their service.
• Optimal Use Cases: Selectel is the go-to provider for users within Russia who prioritize adaptable GPU server leasing arrangements, including the option for uncompromising bare-metal deployments, coupled with swift provisioning capabilities. It is ideally suited for entities that value granular control over their server environment, seek to leverage MIG technology for optimized cost structures, and require a diverse palette of GPU options spanning from high-end enterprise accelerators to formidable consumer-grade cards.

4. MTS Web Services (MWS): Orchestrating GPU-Accelerated Private & Hybrid Clouds on a Robust Telecom Foundation

• GPU Capabilities: MWS, the dynamic cloud services arm of Russia’s preeminent telecommunications conglomerate MTS, furnishes a sophisticated virtual infrastructure augmented by both NVIDIA and AMD GPU accelerators. These computational assets are meticulously tailored to address the demanding requirements of high-performance computing (HPC) and advanced machine learning applications.
• Economic Framework: The pricing strategy at MWS is typically solution-centric, meticulously crafted to meet the nuanced needs of enterprises embarking on private and hybrid cloud deployments. Underpinning this, MTS has declared substantial forthcoming investments in its AI service portfolio, including a significant expansion of GPU cluster capacity, indicative of a strategy focused on delivering tangible value for enterprise-level research and development.
• Complimentary Access: A conventional, broadly available free GPU tier is less probable, aligning with MWS’s pronounced focus on enterprise clientele and operations within regulated industrial sectors. More likely are proof-of-concept engagements or bespoke trial arrangements for appropriately qualified prospective clients.
• Distinctive Attributes & Ecosystem: A cardinal feature differentiating MWS is its officially attested 152-FZ segment. This guarantees that its infrastructure is fully compliant for the processing of sensitive personal data, a non-negotiable requirement for a vast array of Russian organizations. Furthermore, MWS offers container-hosted, GPU-optimized nodes that seamlessly integrate with industry-standard orchestration platforms like Kubernetes and OpenShift. This facilitates the deployment of modern, scalable applications within a secure and efficient framework. The implicit backing of the MTS telecom network ensures robust connectivity and inherent infrastructural reliability. Demonstrating future commitment, MTS has outlined plans to infuse RUB 7.5 billion into AI-centric services throughout 2024, explicitly including the augmentation of GPU cluster capacity.
• Optimal Use Cases: MWS is the provider of choice for Russian enterprises and governmental bodies that necessitate GPU-accelerated private or hybrid cloud architectures governed by exacting 152-FZ compliance. It also strongly appeals to organizations that are progressively embracing containerized application workflows utilizing Kubernetes or OpenShift and value a provider anchored by a resilient national telecommunications infrastructure.

5. VK Cloud Solutions: An Enterprise-Caliber GPU Platform Engineered for AI & Advanced MLOps

• GPU Capabilities: VK Cloud Solutions, an entity with roots in the influential VK Group (a titan of the Russian internet landscape), delivers a Universal Cloud Platform that incorporates GPU instances animated by NVIDIA T4 and V100 graphics cards. These GPUs are judiciously selected for their proficiency in handling data analytics, computer vision tasks, and real-time inference scenarios.
• Economic Framework: The platform operates on an enterprise-focused pricing model, which likely includes provisions for reserved capacity and volume-based discounts, consonant with its comprehensive managed service philosophy.
• Complimentary Access: Specific details regarding a free tier for GPU access are not prominently advertised; enterprise-level trials or structured pilot programs are the more customary methods for evaluation.
• Distinctive Attributes & Ecosystem: VK Cloud Solutions places significant emphasis on delivering a curated, managed service experience. This is exemplified by their provision of automated MLOps pipelines, sophisticated role-based access control (RBAC) mechanisms, and integrated, intuitive monitoring dashboards. Such features collectively streamline the entire AI workflow, from initial data ingestion through to final model deployment, thereby substantially mitigating operational burdens and complexities. Tangible evidence of their platform’s efficacy was demonstrated in pilot programs where VK Cloud achieved up to a threefold acceleration in medical-imaging AI training when benchmarked against CPU-only cluster configurations.
• Optimal Use Cases: VK Cloud Solutions is optimally suited for enterprises operating within Russia that are in search of an enterprise-grade, managed GPU platform replete with sophisticated MLOps capabilities designed to expedite their AI development and deployment lifecycles. It holds particular value for organizations in specialized fields such as healthcare (specifically medical imaging) and any entity that places a high premium on robust system monitoring and granular access control functionalities.

6. SberCloud (Integrated within the Sber Ecosystem): A Fortified Private ML Platform for Highly Confidential AI Endeavors

• GPU Capabilities: SberCloud’s flagship offering in this domain, ML Space, represents a meticulously architected private-cloud environment, expressly conceived for AI workloads of a confidential or sensitive nature. Within this secure enclave, it provides GPU-accelerated virtual machines fortified with high-performance NVIDIA A100s and the versatile T4 GPUs.
• Economic Framework: Pricing is structured for private cloud deployments, typically involving dedicated resource allocation and comprehensive enterprise-level agreements. The overarching focus is on furnishing an exceptionally secure and compliant operational environment for the stewardship of sensitive data assets.
• Complimentary Access: Given the specialized, secure, and private nature of this offering, a standard free tier is not applicable.
• Distinctive Attributes & Ecosystem: ML Space is strategically positioned within the Russian market as an import-substituted solution. This designation underscores its adherence to Russia’s stringent 152-FZ federal law (governing personal data protection) and the internationally recognized ISO 27001 standards for information security management. This robust compliance framework is particularly indispensable for projects within the financial services sector and governmental initiatives. The platform further enriches its secure environment with managed Jupyter notebooks and automated MLOps capabilities. Notably, custom GPU clusters can, according to SberCloud, be provisioned and deployed in less than an hour, all supported by SberCloud’s round-the-clock enterprise support and its extensive network of regional data centers.
• Optimal Use Cases: SberCloud’s ML Space is the definitive choice for financial institutions, governmental agencies, and diverse organizations across Russia that are entrusted with the handling of exceptionally sensitive data. It is for those who mandate a private, rigorously compliant (152-FZ, ISO 27001) GPU-accelerated environment, complete with integrated MLOps tooling and unwavering enterprise-grade support.

7. Rostelecom: Leveraging GPU-Powered Cloud Gaming Infrastructure for Broader AI Applications

• GPU Capabilities: Rostelecom, a cornerstone of Russia’s telecommunications infrastructure, has astutely employed NVIDIA’s GeForce NOW technology as the foundation for its cloud-gaming tariff offerings. This service furnishes users with low-latency connectivity to servers equipped with NVIDIA RTX-class GPUs. The underlying infrastructure is progressively evolving to incorporate more enterprise-focused GPUs such as the NVIDIA L4 and even higher-end accelerators.
• Economic Framework: While the service’s primary market is the gaming community, offering remarkably affordable daily access rates (for instance, around RUB 75 per day), this pricing strategy implicitly signals the availability of GPU resources at potentially highly competitive cost points for other applications.
• Complimentary Access: Cloud gaming services often feature limited free trial periods or highly constrained free usage tiers to attract users.
• Distinctive Attributes & Ecosystem: Although gaming remains the principal application, Rostelecom’s formidable GPU infrastructure—initially built upon high-performance gaming GPUs and now integrating enterprise-grade L4 accelerators—possesses the inherent capability to be repurposed and adapted for AI inference services and innovative streaming-based model deployment architectures. Furthermore, their continuous program of data-center expansion, now characterized by a complete transition to locally sourced hardware components, augurs an even greater reservoir of GPU capacity destined for both entertainment and burgeoning enterprise AI use cases.
• Optimal Use Cases: Rostelecom’s offering appeals to developers and businesses within Russia seeking exceptionally cost-effective access to GPU resources, particularly for inference tasks, real-time streaming applications, or for exploratory AI projects that can ingeniously leverage the architecture of cloud gaming infrastructure. It also merits attention from those tracking the strategic evolution of major telecom providers as they expand into broader AI service platforms.

Navigating the Russian GPU Cloud Constellation: Strategic Decision Factors

The selection of an optimal GPU cloud partner within the Russian Federation is a nuanced process, demanding a meticulous evaluation of specific technical prerequisites, budgetary constraints, and overarching regulatory obligations:

• Harmonizing Computational Power with Task Specificity (Training vs. Inference):
  • For the demanding process of training large, intricate AI models, preference should be given to platforms that furnish high-performance A100/H100-backed clusters. Providers such as Yandex Cloud, Selectel, and SberCloud are particularly well-equipped for these intensive endeavors.
  • Conversely, for cost-efficient and agile inference operations, instances powered by NVIDIA T4/V100 GPUs, available from entities like VK Cloud Solutions and potentially Rostelecom’s repurposed infrastructure, often strike an optimal balance between performance and expenditure.
• Upholding Compliance and Data Security Mandates (Notably 152-ФЗ):
  • When workloads involve the processing of sensitive personal data or fall under the purview of regulated industries, it is imperative to engage providers that offer officially accredited infrastructure segments. SberCloud (through its ML Space) and MTS Web Services (MWS) stand out by providing environments that are demonstrably compliant with 152-FZ, alongside other pertinent standards such as GDPR-equivalents and ISO 27001. For a multitude of Russian organizations, this is a non-negotiable criterion.
• Streamlining DevOps and MLOps Integration:
  • For organizations where seamless infrastructure-as-code (IaC) practices and deeply integrated MLOps pipelines are paramount, Yandex Cloud (with its comprehensive Terraform support and DataSphere studio) and VK Cloud Solutions (offering managed MLOps functionalities) deliver robust frameworks for Kubernetes orchestration, Terraform automation, and fluid, end-to-end AI workflows.
• Maximizing Budgetary Flexibility and Cost Optimization Strategies:
  • Selectel’s innovative MIG (Multi-Instance GPU) slicing capability for its A100/A30 GPUs enables highly granular resource allocation, thereby unlocking significant potential for cost savings. The prevalence of pay-as-you-go billing models (a common feature across numerous providers, including Yandex Cloud) and the potentially disruptive pricing structures emerging from Rostelecom’s gaming-derived service models can present avenues to substantially reduce the effective cost per GPU-hour for particular use cases.
• Ensuring Adherence to Data Residency Imperatives:
  • A salient advantage inherent in utilizing these domestic Russian providers is their intrinsic provision of locally situated data centers. This foundational characteristic guarantees that all data remains physically within the Russian Federation, thereby ensuring full compliance with national data sovereignty legislation.
• Evaluating the Broader Ecosystem and Depth of Managed Services:
  • It is prudent to consider the encompassing ecosystem offered by each provider. Yandex, for instance, presents a rich tapestry of tightly integrated cloud services. In contrast, VK Cloud and SberCloud tend to offer more curated, managed, private-cloud-like experiences. Selectel, on the other hand, often affords users more direct dominion over the underlying hardware.

Epilogue: Catalyzing AI-Driven Progress within Russia’s Sovereign Digital Frontiers

The domestic GPU cloud market within the Russian Federation offers a compelling and increasingly sophisticated array of choices, meticulously tailored to address local operational, regulatory, and strategic imperatives. From hyperscale public cloud platforms armed with advanced, integrated AI development suites, to specialized private cloud sanctums architected for maximal data security and compliance, through to agile providers offering flexible server leasing arrangements, organizations across Russia now have substantive access to the formidable computational power requisite for pioneering AI development.

By conducting a thorough and judicious alignment of your specific workload profile, budgetary parameters, unwavering compliance mandates (with particular emphasis on 152-FZ), and the desired degree of managed service envelopment with the distinct offerings of these indigenous providers, you can effectively and confidently harness high-performance GPU compute. This strategic empowerment ensures that your valuable data assets remain secure and sovereign within Russia’s digital confines, enabling businesses and research entities alike to innovate with assurance and contribute meaningfully to the continued maturation and dynamism of Russia’s digital economy.