Use Cases

Pictor’s GPU Renting service is a flexible solution for a wide range of compute-intensive tasks. Here are some of the most common use cases:

AI Model Training

Training a large AI model, such as a large language model (LLM) or a computer vision model, requires a massive amount of GPU power over a long period. With Pictor Network, you can rent a specific number of GPUs for the required duration to handle this heavy workload. This allows you to accelerate training time and avoid the significant upfront costs of hardware investment.

AI Fine-tuning

When adapting an existing AI model to a new domain or dataset, fine-tuning can require several high-performance GPUs for a shorter duration. Pictor Network makes it easy to rent the exact resources you need for fine-tuning tasks, from a few hours to several days, without long-term infrastructure commitments.

AI Inference

After a model is trained, it needs to be deployed to make real-time predictions or "inferences." This requires a stable and reliable computing environment. On Pictor Network, you can rent GPUs specifically for inference workloads to handle high demand, ensure low latency, and optimize operational costs.

AI Model Hosting

For businesses and developers who need to host AI models 24/7, Pictor Network provides a reliable and cost-effective solution. By renting GPUs for continuous hosting, you can provide uninterrupted service and benefit from flexible scalability without the hassle of hardware maintenance.

3D Rendering

Rendering complex 3D scenes—whether for films, animations, architectural visualizations, or game assets—demands powerful GPUs and massive parallel compute. With Pictor Network, artists and studios can rent GPUs on demand to accelerate rendering across engines like Redshift, Octane, Blender Cycles, and Unreal Engine. This enables faster project turnaround without the need for expensive, high-end workstations.

Generative Workloads

Generative AI tasks like image, video, or 3D content generation (using diffusion or transformer-based models) can be computationally heavy. Pictor Network provides the necessary GPU performance to handle these workloads efficiently, supporting creators, developers, and studios working on generative pipelines.

Simulation & Research

Scientific computing, engineering simulations, and academic research often require bursts of GPU compute for workloads such as fluid dynamics, molecular modeling, or data analysis. With Pictor’s flexible GPU renting model, researchers can quickly access powerful GPUs when needed, optimizing both time and budget.