Build your container from scratch, or use one of our preconfigured templates. All the container needs to do is provide an HTTP endpoint.
Configure your container's CPU, RAM, and disk resources. Rank GPUs by priority, and set the minimum and maximum number of replicas.
We'll handle the rest — autoscaling, load balancing, and redundancy. You'll be ready to send API requests to your new endpoint in minutes.
TensorDock's managed GPU containers are the easiest way to deploy a scalable API endpoint for any use case, and it's available at no additional charge on top of the cost of the compute resources.
Our managed container platform lets you deploy container groups atop any of our massive fleets of GPUs and autoscale with ease.
Uncompromising performance for image and video processing, gaming, and rendering.Deploy a 4090 container
Accelerated machine learning LLM inference with 80GB of GPU memory.Deploy an A100 container
When you spend more than $10,000/month on TensorDock:
A person to ensure that your needs have been met.
Your requests will be placed in a priority queue.
Chat with our team in realtime to resolve issues.
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