Run demanding GPU workloads on dedicated NVIDIA GPU resources with full root or administrator access, multi-GPU configurations, and predictable pricing.
Need high-performance GPU resources without purchasing and maintaining your own hardware?
MaxCloudON provides preconfigured cloud GPU servers with NVIDIA GPUs reserved for your use.
Our GPU servers are suitable for:
Choose from single-node, multi-GPU configurations, install compatible software, and manage your environment with full administrative access.
No setup fees. No GPU resource sharing. No hidden usage charges.
Your assigned GPUs are reserved for your use and are not shared. Choose from preconfigured NVIDIA GPU configurations.
Run AI frameworks, rendering engines, simulation software, and CUDA-enabled applications on dedicated GPU infrastructure.
Configure your operating environment and install compatible software, frameworks, drivers, and production tools.
Choose daily, weekly, or monthly plans with defined GPU, CPU, memory, VRAM, and storage specifications. No setup fees.
Select a configuration and access your GPU server within minutes.
Move to another GPU configuration or activate additional GPU servers when your workload grows.
Use your GPU server for a day, a week, a month, or longer without a mandatory long-term commitment.
Receive help with server access, connectivity, infrastructure-related issues, and configuration of the provided environment.
MaxCloudON GPU servers support production workloads requiring dedicated GPU resources, high VRAM capacity, and full control over the software environment.
Train, test, and run machine learning models using frameworks such as TensorFlow, PyTorch, Keras, Scikit-learn, and Hugging Face Transformers.
Run GPU-accelerated simulations, engineering calculations, physics workloads, computational modelling, and data-intensive processing.
Build a custom rendering environment with control over software versions, plugins, assets, and render settings.
Run encoding, transcoding, image processing, computer vision, and post-production workloads on dedicated GPU resources.
GPU requirements vary depending on software, workload size, VRAM usage, model architecture, render engine, and expected processing time.
We will recommend an available GPU configuration based on your requirements.
“The fastest dedicated VPS we have used. The rendering nodes are really dedicated and you’ll get what is advertised. It’s applicable, from a small freelance artist to a big design studio.”
Principal/Creative Director of Clusters Creative
“We have used the services of Rend-it (now MaxCloudON) many times when we have not been able to meet the deadline with what we have in our in-house Render farm. Quick and responsible, they have always saved us.”
Founder and CEO of Vaya Studios
“Best cloud. Excellent service and support, awesome pricing. There are no restrictions on the installed software. Once the servers were configured, my company used them for months without making any changes.”
Information Technology Manager at Visual Method
Available GPU servers are normally provisioned within minutes after the selected plan is activated.
No. MaxCloudON GPU servers are available with daily, weekly, or monthly prepaid pricing.
Each plan includes defined GPU, CPU, RAM, VRAM, storage, and pricing specifications for the selected rental period.
Yes. The GPUs assigned to your server are reserved for your use and are not shared with other customers.
The server operates within a virtualized environment, but the listed GPU resources remain allocated to your server for the duration of the active plan.
Yes. MaxCloudON GPU servers operate within a virtualized environment.
However, the assigned GPU, CPU, RAM, and storage resources are reserved for your server and are not oversubscribed across multiple customers. This provides more predictable performance than conventional shared or fractional GPU cloud services.
Yes. You receive root access on Linux or administrator access on Windows.
You can install compatible AI frameworks, CUDA-enabled applications, render engines, development tools, libraries, drivers, and production software.
You are responsible for software licensing, compatibility, configuration, updates, security, and application administration.
GPU hardware is provided through predefined server configurations and cannot normally be added dynamically to an active plan.
You can move to another available configuration with a different GPU count or activate additional GPU servers when your workload grows.
The right configuration depends on the software, workload type, GPU model, VRAM requirement, number of GPUs, system RAM, and expected processing time.
For AI workloads, consider model size, training method, batch size, precision, and whether the framework supports multiple GPUs.
For rendering workloads, consider render-engine compatibility, scene complexity, texture usage, VRAM consumption, and multi-GPU support.
Contact our team with your software and workload requirements if you need help choosing an available configuration.
No. Multi-GPU scaling depends on the software, framework, render engine, model architecture, and workload configuration.
Some applications can use multiple GPUs efficiently, while others may use only one GPU or require additional configuration.
Confirm that your application supports the selected GPU model and number of GPUs before choosing a multi-GPU server.
Need deeper details about our billing and payments, file retention policies, software usage, or network security? Visit our centralized MaxCloudON FAQ Platform Hub .
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