We're pleased to announce a series of new GPU-backed instances available on both Core and Gradient featuring NVIDIA's Ampere microarchitecture!

Introducing all-new Ampere instances! announcement 

Announced in mid-2020, Ampere is the codename for NVIDIA's latest line of GPU accelerator cards. Competition for these cards has been fierce and we're happy to bring you four flavors of Ampere, anchored by the top-of-the-line A100.

In addition to the instances listed, we've also introduced 2-way, 4-way, and 8-way configurations for these cards. 

The full table of instances on Paperspace has been updated in the docs. In general, any instance made available on Core will arrive in Gradient shortly thereafter.

Multi-GPU also comes to Windows machines improvement  

One thing you might have noticed already is that multi-GPU instances in Core are no longer exclusive to Linux. You can now spin-up any multi-GPU instance on a Windows machine!

Check out the Paperspace console to get started. 

Model-backed deployments in Gradient Deployments improvement  

We added an important feature to Gradient Deployments: model-backed deployments! 

It's now possible to inject a model at deployment runtime which means Gradient is now able to fetch a model from the Gradient model registry directly. Models can also be referenced from an external S3 bucket.

For more information, read the docs or reach out if you'd like a demo!

State persistence bugs in Gradient Notebooks improvement  

We made substantial improvements to the way that application and cell state is managed in Gradient Notebooks. 

Previously, if you navigated away from a notebook while a cell was running and then returned to the notebook, the cell would sometimes lose its state. We're happy to have implemented a substantial fix to this issue and a number of other issues influencing state management.

If you have feedback for us, please drop us a line!