Fast Inference with Responsive Auto-Scaling
Cost-Effective Inference Solutions
Optimized for Performance and Cost
From optimized GPU usage and auto-scaling to sensible resource pricing, we designed our solutions to be cost-effective for your workloads. Plus, you have the flexibility to configure your instances based on your deployment requirements.
Bare-Metal Speed and Performance
We run Kubernetes directly on bare metal, giving you less overhead and greater speed.
Scale Without Breaking the Bank
Spin up thousands of GPUs in seconds and scale to zero during idle time, consuming neither resources nor incurring billing.
No Fees for Ingress, Egress, or API Calls
Pay only for the resources you use and choose the solutions that enable you to run as cost-effectively as possible.
Modern Inference Platform
Better Performance, Lower Latency
Our inference service offers a modern way to run inference that delivers better performance and minimal latency while being more cost-effective than other platforms.
AUTOSCALING
Optimize GPU Resources for Maximum Efficiency
Auto-scale containers based on demand to quickly fulfill user requests significantly faster than depending on scaling of hypervisor-backed instances of other cloud providers. As soon as a new request comes in, requests can be served as quickly as:
· 5 seconds for small models
· 2.1 seconds for GPT-J
· 3.2 seconds for GPT-NeoX
· 4.3-60 seconds for larger models
SERVERLESS KUBERNETES
Simplified Model Deployment
KServe enables serverless inferencing on Kubernetes with an easy-to-use interface for common ML frameworks like TensorFlow, XGBoost, scikit-learn, PyTorch, and ONNX to solve production model serving use cases.
Specialized GPU Cloud Provider