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GPU
GPU is a way to accelerate your projects without the need to invest in expensive hardware. You gain on-demand access to computing power - wherever and whenever you need it.
Cost optimization
No overpaying - use GPU power at a great price, paying only for what you actually consume. Zero hidden fees, zero unnecessary hardware investments.
Quick start
Ready-to-use environments with ML and CUDA libraries. Launch GPUs in minutes via an intuitive dashboard, API, or popular automation tools.
Choose from multiple GPU generations
Select from the latest compute accelerators (A100, T4, L4, and others) tailored to your specific use cases.
High-performance CPU and storage
Combine GPUs with powerful CPUs and ultra-fast NVMe drives to achieve maximum data throughput.
Load-adaptive scaling
Scale your instances both horizontally and vertically, flexibly adjusting to your project phase and computing power requirements.
No code changes needed
Your applications run natively on GPU instances - no refactoring or modifications required.
Compatible with the ML ecosystem
Supports popular frameworks and libraries such as TensorFlow, PyTorch, JAX, Keras, and many others.
Preconfigured images or custom containers
Choose from ready-to-use GPU environments or deploy your own container images within minutes.
Train and test models with maximum efficiency - even when working with large datasets and complex architectures.
Accelerate rendering times for animations, 3D scenes, and visual projects, regardless of scale.
Process and transcode 4K+ video content without needing your own hardware infrastructure.
Conduct complex numerical calculations, CFD models, FEM analyses, and cloud-based scientific research.
GPU is not included in the standard services accessible through the Oktawave Platform dashboard.
We’ll tailor a solution precisely to your needs.
Get in touch with us
What to Choose?
GPU
On-premises GPU
high upfront costs (hardware, cooling)
deployment can take several months
scaling is complex and expensive
maintenance performed by internal teams
hardware lifecycle of 3 to 4 years
GPU
Cloud GPU
no upfront costs — pay only for the time you use
deployment in just a few minutes
on-demand scalability
maintenance handled by our team of engineers
access to the latest GPU generations
Launch GPU environments within minutes. Train AI models, render graphics, and process data - all without hardware costs or delays.
Access cutting-edge GPUs without the need to invest in physical hardware or handle maintenance.
GPUs accelerate machine learning, rendering and data processing, shortening project completion times.
Built on managed platforms featuring automatic scaling, monitoring, high availability and data center-level security.
Instances are deployed close to end users, ensuring lower latency and better responsiveness.
Environments adhere to ISO/IEC standards, SOC 2, and GDPR, guaranteeing data security and regulatory compliance.
Pay only for the resources you consume - no upfront costs, depreciation, or risk of obsolete hardware.
For innovation leaders
FinTech
Credit scoring, risk analysis, fraud detection
MedTech
Medical image analysis, predictive modeling
Architecture & Animation
Renderings, visualizations, 3D production
Industry & Engineering
Numerical modeling, process simulations
Media & Entertainment
Editing, processing, post-production of video content
Offering
Processors
Including NVIDIA A100, L4, T4
Frameworks
Support for popular frameworks: PyTorch, TensorFlow, JAX, ONNX
System images
Prebuilt images with CUDA and essential libraries preinstalled
Integration
Seamless integration with Docker, Kubernetes, Terraform
Infrastructure
High-performance NVMe storage, fast networking, low latency
Scalability
Flexible instance selection: 1, 2, or more GPUs per machine
Looking for the best solution?
We’ll prepare a tailor-made proposal based on your project’s needs. Along with access to GPU resources, you’ll also receive full support with migration.
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