Azure vs AWS for AI
There is no single winner, there is a winner for your workload
Ask "what is the best cloud platform for AI startups" and every listicle hands you a ranking. The honest answer for a UAE startup is narrower: the right platform is the one that fits your budget, your specific AI use case, and where your data is allowed to live. Azure and AWS both run the same NVIDIA GPUs, both offer managed AI services, and both have a data centre region inside the Emirates. The difference sits in pricing structure, single GPU access, the tools wrapped around the hardware, and how each handles UAE compliance.
Rounak Computers has advised UAE businesses on cloud since 2004, and we hold Gold partner status with both Microsoft and Amazon, so this comparison is written to help you decide, not to sell you one logo. Below you get the GPU options, the real per hour costs, the hidden charges, startup credits, and a checklist you can act on the same day.
What actually decides the "best" platform
On demand GPU time is the single biggest line item. A platform that saves you 20% per GPU hour changes your runway more than any feature list.
Training a model from scratch, fine tuning an open model, or serving inference are three different bills. The cheapest GPU for one is the wrong GPU for another.
A single GPU today can become a 64 GPU cluster next year. Check that your starter instance family scales without a full re architecture.
Healthcare, government and finance data often has to stay inside the UAE. That requirement can decide the platform before price ever enters the conversation.
Raw GPUs are only half the story. The training, deployment and model catalogue tooling around them decides how fast a small team ships.
Free credits can cover your first year of compute. The size and eligibility of each programme differ enough to influence which platform you start on.
GPU options on Azure and AWS
Both clouds sell access to the same NVIDIA silicon: the A100 for mid scale training and fine tuning, the H100 for large scale training and low latency inference, and cheaper cards such as the A10 or T4 class for lightweight serving. The families and, importantly, the minimum sizes differ.
Microsoft Azure GPU families
- ND series (ND A100 v4, ND H100 v5): SXM A100 and H100 GPUs with InfiniBand, built for distributed training across many GPUs.
- NC series (NC A100 v4, NC H100 v5): general machine learning and inference. The single H100 NC H100 v5 is the cheapest H100 Azure offers.
- NV series (A10, L40S): visualisation and cost effective inference for smaller models.
- Single GPU A100 access: Azure lets you rent one A100, useful for jobs that do not need eight.
For teams already on Microsoft 365 and Entra ID, our Azure cloud services in Dubai team can wire GPU workloads into an existing tenant so identity and billing stay in one place.
Amazon Web Services GPU families
- P5 (NVIDIA H100): the p5.48xlarge packs 8 H100 GPUs with 640 GB HBM3 and fast EFA networking for large model training.
- P4d (NVIDIA A100): the workhorse for production training and inference, sold only as an 8 GPU node.
- G5 (NVIDIA A10G): the budget friendly pick for inference and development.
- Inf2 and Trn1: AWS custom Inferentia and Trainium chips that can cut inference and training cost for supported models.
If you want that stack configured for the UAE, our AWS setup for businesses in the UAE covers instance selection, quotas and networking.
GPU pricing, and the costs that hide in the bill
Headline hourly rates are only the starting point, but they still matter. The figures below are recent on demand, per GPU list prices in US regions. UAE region pricing runs higher because of power, tax and network costs, so treat these as a relative guide rather than an exact UAE quote.
| On demand, per GPU per hour | Microsoft Azure | AWS |
|---|---|---|
| NVIDIA A100 | about $4.41 | about $3.43 (8 GPU minimum) |
| NVIDIA H100 | about $8.30 (single NC H100 v5 about $6.98) | about $6.88 (P5) |
| Single GPU rental | Yes, A100 and H100 | No, 8 GPU node for A100 and H100 |
| Spot discount | 70 to 82% off, 30 second eviction notice | large discount, 2 minute eviction notice |
| Reserved or savings commitment | roughly 40 to 60% off | roughly 40 to 60% off |
Rates move often and vary by region and configuration. Confirm live pricing in each provider's calculator before you budget.
Moving data out of the cloud is billed per gigabyte. Downloading model weights or serving a high traffic API can add hundreds of dollars a month. Keep data in one region.
Billing runs whether the GPU is training or sitting idle between runs. Without job scheduling, a large slice of the bill is empty capacity.
On Azure, stopping a VM without deallocating it still charges for compute. Scripts should explicitly deallocate to stop the meter.
A faster H100 at a higher hourly rate can finish a training job in a fraction of the time, so the total cost is lower even though the sticker price is higher.
Managed AI services and startup credits
GPUs are the engine, but managed services decide how fast a lean team ships. On Azure that means Azure Machine Learning for the training and deployment pipeline, the Azure AI model catalogue, and Azure OpenAI Service for running GPT class models inside your own network. On AWS that means Amazon SageMaker for the end to end workflow and Amazon Bedrock for hosted foundation models, with Inferentia and Trainium for cheaper serving.
As a Gold partner with Microsoft, Huawei and Amazon, and one of nine businesses awarded the Dubai AI Seal by the Government of Dubai in April 2025, Rounak's certified engineers work across both stacks, so the recommendation follows your workload rather than a single vendor relationship.
- Founders tier: $1,000 in credits, self serve, no investor needed
- Portfolio tier: up to $100,000 through a qualifying VC or accelerator
- Generative AI tier: up to $300,000 for eligible AI startups
- Credits usable against SageMaker, Bedrock and EC2 GPU instances
- Founders Hub: $1,000 instant, up to $5,000 after verification
- Investor path: up to $150,000 in Azure credits
- Includes GitHub Enterprise, Microsoft 365 and Azure OpenAI access
- Entry tiers need no accelerator or referral to start
Programme amounts and eligibility change quarterly. Many founders apply to both and keep the second platform's credits in reserve.
The local angle most guides skip
Data residency, compliance and UAE regions
For healthcare, education, government and finance workloads, where the data physically sits can outrank price. Both hyperscalers now run a region inside the Emirates, so you do not have to route sensitive data offshore.
- AWS Middle East (UAE), me-central-1: launched in 2022 with three availability zones, data stored and processed in the UAE.
- Azure UAE North (Dubai): launched in 2019 with three availability zones, paired with UAE Central, data held at rest in the UAE.
- Azure OpenAI in UAE North: lets prompt and response processing for GPT class models stay within UAE borders.
Keeping workloads in a local region also supports your obligations under the UAE Personal Data Protection Law. If compliance is driving the decision, our guide to data localization and privacy laws in the UAE breaks down the cross border transfer rules your IT team should plan around.
Which cloud fits common UAE startup scenarios
Serving a small model on a tight budget favours AWS G5 or Inferentia, or a single A100 on Azure so you are not paying for an 8 GPU node.
Multi GPU H100 clusters on either cloud. Let your startup credit balance and spot availability decide, since the hardware is the same.
Already on Microsoft 365, Entra ID or .NET? Azure plus Azure OpenAI keeps identity, billing and models in one tenant.
Healthcare, government or finance data that must stay onshore points to the local UAE region on whichever platform, with PDPL controls in place.
If your shortlist also includes Huawei or Alibaba Cloud, our comparison of cloud platforms available in the UAE sets the wider context alongside Azure and AWS.
Azure vs AWS at a glance
| Dimension | Microsoft Azure | AWS |
|---|---|---|
| Single GPU A100 or H100 | Yes | 8 GPU node only |
| Custom AI silicon | GPU only | Inferentia and Trainium |
| Flagship managed AI | Azure ML and Azure OpenAI | SageMaker and Bedrock |
| Startup credit ceiling | up to $150,000 | up to $300,000 (AI tier) |
| UAE region | UAE North, since 2019 | me-central-1, since 2022 |
| Best first fit | Microsoft aligned teams | breadth and budget inference |
Stretch the budget
Cost saving tips that work on both clouds
These habits routinely cut a GPU bill by half or more without touching model quality.
- Use spot or preemptible instances for training that can tolerate interruption
- Commit to reserved capacity or savings plans for steady, predictable workloads
- On Azure, deallocate rather than stop so idle VMs stop billing compute
- Keep data and compute in the same region to avoid egress charges
- Right size the GPU: an A100 often beats an H100 on cost for models under 13 billion parameters
- Consider Inferentia or Trainium on AWS for supported serving workloads
- Rent a single GPU on Azure for small jobs instead of an 8 GPU node
- Stack startup credits and set cost alerts before, not after, the first big bill
A checklist to choose the right platform
Write down whether you are training, fine tuning or serving inference, and the rough model size.
Decide the most you can spend per month, then map GPU hours against it before you provision.
Confirm whether your data must stay in the UAE, then shortlist the local region on each platform.
Apply for startup credits, run a small pilot, measure real cost per outcome, then reserve capacity.
Frequently asked questions
Is Azure or AWS cheaper for GPUs?
It depends on the GPU and the job. On recent list prices AWS is a little cheaper per GPU for the A100 and H100, but AWS sells those cards only in 8 GPU nodes, so for a job that needs one or two GPUs Azure's single GPU option can end up cheaper overall. For steady workloads, reserved pricing on either cloud saves roughly 40 to 60%.
Which cloud is better for a startup building on OpenAI models?
Azure has a direct advantage here through Azure OpenAI Service, which lets you run GPT class models inside your own Azure network and, in the UAE North region, keep prompt and response data within the country. AWS answers with Amazon Bedrock, which hosts a range of foundation models. If your product is tied to OpenAI specifically, Azure is usually the smoother path.
Can I keep my AI data inside the UAE?
Yes. AWS runs the Middle East (UAE) region me-central-1 with three availability zones, and Azure runs UAE North in Dubai with three availability zones. Both store data at rest inside the Emirates, which supports your obligations under the UAE Personal Data Protection Law for sensitive healthcare, government and finance workloads.
How much can startup credits actually save me?
AWS Activate ranges from $1,000 self serve up to $100,000 through a qualifying VC or accelerator, with an AI tier reaching up to $300,000. Microsoft for Startups starts at $1,000 instant, up to $5,000 after verification, and can reach up to $150,000. Credits typically cover a startup's first year of GPU and managed service usage, though they expire, so plan the transition to paid usage early.
Do I have to choose only one platform?
No. Many UAE startups run primary workloads on one cloud and keep credits or specific services on the other, for example training on one platform and serving inference where it is cheapest. A multi cloud setup adds some operational overhead, so it is worth doing deliberately rather than by accident.
What is the most common mistake that inflates a GPU bill?
Idle time and egress. GPUs bill whether they are working or not, so unscheduled instances quietly burn credits, and moving large datasets or model weights out of the cloud adds per gigabyte charges. On Azure there is a second trap: stopping a VM without deallocating it still charges for compute.
Can Rounak Computers set this up and support it locally?
Yes. Rounak Computers is a Dubai based provider on Khalid Bin Al Waleed Road in Bur Dubai, with a full time team of certified in house engineers and 24/7 support. As a Gold partner with both Microsoft and Amazon, we give vendor neutral advice, configure the GPU workloads, and manage them on either platform once they are live.
Not sure which fits your workload?
If you would rather pilot before you pick, a structured plan makes the move painless. Our cloud migration services in Dubai cover instance selection, data residency and cost controls on both Azure and AWS.
