Check out what's new on Hyperstack this week:
You can now create and attach volumes in the US-1 region!
This means persistent storage is available for all your VMs deployed in this region, ideal for workloads that need to retain data across reboots.
Planning to use Spot flavors?
You’ll now see a warning icon on flavor cards during VM and Cluster deployment. This gives you a heads-up that Spot VMs may be interrupted, so you can make informed choices.
Check out our latest blog on Hyperstack:
With new releases now and then, AI models get bigger, training gets more complex and inference workloads become more demanding. But here's the catch: not all GPUs can keep up with the demands. Choosing the wrong one can slow down your progress, eat into your budget or worse, affect your model performance. That's why you need the right GPU recommendations for AI tailored to your workload. In this blog, we explore the best GPUs for AI. Check out the full blog here.
The recent surge of open-source LLMs like Meta’s Llama models and Mistral AI’s Mistral 7B has made it easier for startups to obtain cutting-edge model architectures. However, training these models comes with massive costs and operational challenges. In this blog, we’ll break down challenges startups face when training models and explore how Hyperstack can help manage and reduce these costs. Check out the full blog here.
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See how users turn big ideas into real results with Hyperstack for their AI and GPU-heavy workloads. Got your success story? We'd love to hear it and you might just see it featured in our next newsletter!
That's it for this week's Hyperstack Rundown! Stay tuned for more updates next week and subscribe to our newsletter below for exclusive AI and GPU insights delivered to your inbox!
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