Alex Medick

10 key questions executives should ask before choosing an AI cloud provider - performance, pricing, support, and why AMD MI325X matters.

10 Questions to Ask Before Choosing an AI Cloud Provider

Choosing the right AI cloud provider isn’t just a technical decision, it’s a strategic one. Whether you’re training frontier models or scaling production inference, the wrong infrastructure can slow you down, balloon costs, or box you into a platform that can’t evolve with your needs.

Here are the 10 key questions every C-suite leader, founder, or technical executive should ask before locking into an AI cloud partnership.


1. Is the infrastructure optimized for AI, or just repurposed general c

Choosing the right AI cloud provider isn’t just a technical decision, it’s a strategic one. Whether you’re training frontier models or scaling production inference, the wrong infrastructure can slow you down, balloon costs, or box you into a platform that can’t evolve with your needs.

Here are the 10 key questions every C-suite leader, founder, or technical executive should ask before locking into an AI cloud partnership.


1. Is the infrastructure optimized for AI, or just repurposed general cloud?

Many clouds were built for general computing. As AI interest increased, legacy cloud providers made it an add-on feature, not a purpose-built one. Ask if the provider offers purpose-built infrastructure, like AMD MI325X GPUs, designed specifically for AI and HPC workloads. At TensorWave, we’ve engineered our platform from the ground up to support memory-intensive, large-scale AI.

➡️ Learn how we optimize AI performance with MI325X.


2. What’s the GPU memory per instance?

If you’re training LLMs or fine-tuning multimodal models, memory is everything. MI325X offers 256GB of HBM3e per GPU (2x the memory of H100s) letting you run larger models with fewer GPUs, reducing both complexity and cost.

➡️ Read: Bigger Models, Fewer GPUs


3. Can I get dedicated infrastructure or am I sharing resources?

Latency, jitter, and noisy neighbors kill performance. You want dedicated compute, not VMs shared across unknown tenants. TensorWave delivers exclusive infrastructure, tuned and locked for your workload.

➡️ Explore our Dedicated Compute architecture.


4. How fast can I scale up or down?

AI workloads are dynamic. You need a partner that can scale clusters up or down instantly, without weeks of lead time. We offer dynamic, elastic provisioning with the ability to spin up large MI325X clusters in minutes.

➡️ See our Scalable Cluster approach.


5. Do they offer white-glove support, or am I on my own?

Support isn’t a Slack channel with bots. When infrastructure is mission-critical, you need real experts who understand AI workloads and can troubleshoot in real time. TensorWave customers get dedicated support from engineers—not ticket queues.

➡️ Discover our white-glove onboarding.


6. What’s the pricing model and can I avoid egress fees?

Look for transparent, predictable pricing with no hidden fees. Many clouds punish you with data egress charges. We offer flat-rate pricing and zero-cost egress to give you peace of mind and budget clarity.


7. Are they locked into one hardware vendor or do I have optionality?

Vendor lock-in can limit your roadmap. TensorWave is an exclusive AMD-native AI cloud, unlocking performance, price/performance, and availability advantages NVIDIA clouds can’t match. Plus, open ecosystems like ROCm keep you agile.

➡️ Read: Why Infrastructure Optionality Is the New Moat.


8. Can they support real-time inference as well as training?

Many clouds are designed only for training, not low-latency inference. TensorWave supports both—with deterministic caching, high-throughput networking, and massive VRAM for real-time AI agents and longer-context LLMs.

➡️ Dive into: AI Inference at Scale.


9. What’s their availability and uptime guarantee?

Downtime isn’t just annoying, it’s expensive. Ask about SLAs, power redundancy, and networking resilience. TensorWave operates out of enterprise-grade facilities with high-availability guarantees and multi-region options.


10. Do they align with your values on speed, innovation, and control?

Choosing an AI cloud provider is like choosing a co-founder for your infrastructure. Make sure their roadmap, values, and pace match yours. At TensorWave, we’re builders first, obsessed with speed, obsessed with performance, and committed to helping you win.


Final Thought

In a world where compute is the new oil, your cloud provider isn’t just a vendor, they’re a strategic edge. Ask the tough questions. Demand better answers.

And if you’re ready to explore what an AMD-native, white-glove AI cloud built for scale really looks like—we’d love to talk.


About TensorWave

TensorWave is the AMD AI cloud purpose-built for performance. Powered exclusively by AMD Instinct™ Series GPUs, we deliver high-bandwidth, memory-optimized infrastructure that scales with your most demanding models—training or inference.

Ready to get started? Connect with a Sales Engineer.

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10 Questions to Ask Before Choosing an AI Cloud Provider

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