TABLE OF CONTENTS
NVIDIA H100 SXM On-Demand
Welcome to Hyperstack Weekly Rundown
The GPU race doesn’t slow down and neither do we. A new region, smarter inference, AI Image Playground and Auto Top-Up are all part of what’s coming up on Hyperstack.
Take a few minutes to catch up on everything.
New Hyperstack Region: EU-1 is Now Live
Built from the ground up for next-generation AI workloads, the EU-1 region delivers the power density, advanced cooling and physical capacity required to run the latest NVIDIA platforms at scale. With strong early demand, all Phase 1 capacity has already been fully reserved.
Expansion is already underway. In partnership with Glesys, we’re bringing additional NVIDIA Blackwell and Blackwell Ultra capacity online later this year to support growing customer needs.
If you're planning upcoming deployments, now is the time to get ahead of demand. We’re currently taking expressions of interest for future capacity. Reach out to discuss your requirements at sales@hyperstack.cloud.
Coming Soon
AI Studio Image Playground
We’re bringing image generation and editing to AI Studio. Create images from text, transform existing visuals and switch seamlessly between text-to-image and image-to-image workflows. All powered by state-of-the-art vision models.
Stay tuned for what’s coming next.
Auto Top-Up
Never run out of credits mid-workflow again. Auto Top-Up will keep your balance topped up automatically the moment it hits your set threshold. Set your limit, choose your top-up amount and keep building as your compute stays ready.
Launching beta customers next week, with GA to follow.
New on our Blog
Check out the latest blogs on Hyperstack:
Managed Kubernetes vs Managed SLURM:
Which Orchestrator Fits Your AI Workloads
Orchestration is not a deployment detail; it is the layer that determines whether your training runs hit theoretical throughput or loses half of it to scheduling contention, broken GPU allocation, and inter-node coordination failures. The Kubernetes vs SLURM decision compounds across every run you ship.
5 Inference Optimisation Techniques:
To Improve Performance
The model passes evaluation but latency is 3× too slow for production. This is where real inference work starts. Making a model accurate is a research problem; making it fast and efficient is an engineering problem with well-understood solutions.
How to Run Cost-Efficient Inference Workloads:
A Step-by-Step Guide
Cost-efficient LLM inference on Hyperstack or any GPU cloud means maximising tokens per dollar by optimising every layer of the stack. In practice, that includes right-sizing GPUs, applying quantisation, optimising KV cache, using modern runtimes such as TensorRT-LLM, vLLM and TGI, batching well, autoscaling dynamically and tracking the right metrics, often delivering 2×–10× cost savings in production.
When to Choose Dedicated Private Cloud:
A Decision Framework
Your model is ready and the team has delivered. Then InfoSec asks where the data lives and deployment stalls. Not because the infrastructure failed, but because you cannot prove it didn’t. This guide explains where these gaps come from, what compliance teams actually need to see and how to design infrastructure that holds up under scrutiny.
Distributed Inference Explained:
When Enterprise Teams Need It
Most teams only think about distributed inference when something breaks: latency spikes, GPUs max out or queues back up. By then, it’s no longer a design decision, it’s an incident. This guide explains when distributed inference actually becomes necessary, what signals to watch for and how to approach it as an architectural choice, not a last-minute fix.
Help Shape the Future of Hyperstack
Great products are built with the people who use them. If there’s something you would like to see on Hyperstack whether it is a new feature, workflow improvement or integration that would make your work easier, we would love to hear about it.
Your feedback helps us prioritise what matters most and build a platform that works better for the community.
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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