Linode is a legacy cloud hosting provider that introduced GPUs in mid-2019. Linode has a single GPU model available (NVIDIA Quadro RTX 6000) and although it's an excellent choice in terms of value and performance, the limitations of only a single GPU type are substantial. There will be a negative impact on reproducibility, flexibility, and vendor lock-in.
Paperspace meanwhile has been specializing in cloud GPUs since 2016 and offers a wide array of GPUs at tiers above and below the RTX 6000. In particular, Paperspace offers the RTX 4000 and RTX 5000, which offer similar levels of price-to-performance as the RTX 6000.
Linode has long specialized in cloud hosting for websites. Paperspace specializes in serving high-end GPU compute.
Linode limits multi-GPU configuration of the sole RTX 6000 instance to 1x, 2x, or 4x. By contrast, Paperspace offers 8x of number of different GPUs including the ultra-powerful A100 40 GB and 80 GB configurations which are specifically geared towards deep learning.
Linode offers a single GPU type that is not supported by any of the other major cloud providers. While the RTX 6000 is a solid pick for value and performance, there are compatibility and reproducibility risks involved with using a GPU that is difficult to find. Paperspace meanwhile has more than a dozen different GPU machines -- most of which are replicated across a couple other GPU cloud providers.
The Linode GPU offering is tailored towards existing Linode customers who have developed a need for GPUs. Paperspace GPUs are targeted towards developers and teams who need GPUs from the very beginning.
There are a lot of reasons to recommend Linode (and Linode traditionally scores well in customer satisfaction scores) but it does not appear that Linode is up-to-date in the world of GPU cloud providers.
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"First time using @HelloPaperspace. Great way to spend more time learning and practicing ML rather than debugging / setting up a Cloud instance."
"We're testing deployment to @HelloPaperspace GPU cloud. So far it works great! Next week we'll add possibility to launch http://SIML.ai instance on it through Model Engineer - one click and you'll be up-and-running!"
