Shakti’s serverless GPUs support popular machine learning and AI frameworks like TensorFlow, PyTorch, and CUDA, enabling seamless deployment of models across multiple libraries.

Yes, Shakti supports bring-your-own-container (BYOC) functionality, allowing you to deploy custom models using containerized environments. You can upload your Docker container and run your model in our serverless GPU infrastructure.

Serverless GPUs are billed based on the duration of GPU usage per second. You are charged for the actual time your model is running, ensuring cost efficiency and scalability without over-provisioning.

Shakti’s serverless GPUs auto-scale dynamically based on the number of requests, latency or throughput. This ensures that resources are efficiently utilized without manual intervention.

Shakti’s serverless GPU infrastructure is built with high availability in mind, featuring fault-tolerant execution, automatic job restarts, and multi-region redundancy to minimize downtime.