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More than once I had a question and support helped me in minutes, not only fast but so so friendly. On top of all that they somehow to manage to provide
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I've used it for
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!!! Cost approx $80usd for the GPU rental.
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See how it works ?
Why choose Us ?
24X7 Customer support
Deep Learning is hard, need help or stuck somewhere? just say Hi!👋
More cash in your pockets
Pay per minute and start for as low as $0.19
Powerful API
Use API to automate training, deployment of your AI pipelines.
Deploy
Deploy apps like Gradio, Streamlit, fastapi and more on GPU powered instances.
Get started
A simple UI to set up a GPU powered instance in few clicks.
Performance
Choose from world's fastest Nvidia GPU A100, A6000 and A5000.
Flexible
Choose a predefined instance / public container. Access instance through Jupyter Lab, VScode or SSH
Scalable
Increase/Decrease GPU, switch to a different GPU type for faster training.
Powerful API
Quickly automate your instance lifecycle for training and deploying your AI model using our python API.
//Instantiate blazing fast GPU with your favourite ML library/framework.
instance = Instance.create(gpu_type='A100',
num_gpus=1,
hdd=20,
framework_id=0,
script_id=1)
//Running Instances
instance.url //Get JupyterLab URL
instance.ssh_str // Get SSH string to connect to VS code
//Free up GPU/memory resources while persisting all data and models to disk
instance.pause()
//Scale up number of GPU or switch to faster one while resuming your GPU instance
instance.resume(num_gpus=4,
gpu_type='A100',
hdd=200)
// Free up the resources and stop billing.
instance.destroy()
Create Instance
Instantiate blazing fast GPU with your favourite ML library/framework.
Connect to Instance
Connect to JupyterLab or VScode through SSH.
Pause Instance
Free up resources GPU and memory while persisting all data and models to disk.
Resume Instance
Increase number of GPU or switch to faster one to train your workload efficiently while resuming GPU instance.
Delete Instance
Free up the resources and stop billing. Deletes the data and models