ChatGPT
Claude
Perplexity
Gemini
Meet your local partner
At a glance
- NVIDIA AI Enterprise: $4,500/GPU (1 year), $13,500 (3 years), $18,000 (5 years).
- Cloud marketplace option: $1 per GPU per hour plus instance cost.
- Compare the same task, answer quality and service level.
Cloud AI vs an on-premises NVIDIA deployment
Swipe or scroll sideways to compare all options.
| Buying difference | Azure hosted AI model service | Google Cloud hosted model service | On-premises deployment using NVIDIA AI Enterprise |
|---|---|---|---|
| Published universal token price | None; select model, region, deployment type, and input/output rates | None; select model, region, processing mode, and input/output rates | Not inherently token-priced; calculate cost from deployed capacity and utilization |
| Software price reference | Included or separately charged according to the selected service | Included or separately charged according to the selected service | NVIDIA lists a standard one-year AI Enterprise subscription at $4,500/GPU; special programs differ |
| Purchase unit | Model-specific usage or provisioned capacity | Model-specific usage or provisioned throughput | Server/GPU capacity, software licenses, and operations |
| Model choice | Models offered in the selected Azure service and region | Models offered in the selected Google service and region | Models compatible with local hardware and permitted by their licenses |
| Hardware ownership | No local model server required for the managed endpoint | No local model server required for the managed endpoint | Business buys or leases supported compute, storage, and networking |
| Capacity during low usage | Usage billing can suit intermittent work; other resources may keep charging | Usage billing can suit intermittent work; other resources may keep charging | Hardware and operating costs remain even when utilization falls |
| Data control | Contract, region, deployment, retention, and access settings matter | Contract, region, deployment, retention, and access settings matter | Local hosting allows direct infrastructure control; security still requires implementation |
| Operations responsibility | Vendor operates the hosted model service; business operates its application and access | Vendor operates the hosted model service; business operates its application and access | Business/provider operates the model stack, hardware, updates, and application |
| Main limitation / extra cost | Token/capacity charges are only part of the application bill; region and model matter | Input/output rates, processing mode, retrieval and storage can change total cost | $4,500/GPU/year is software only; hardware, power, operations and redundancy are extra |
| Best fit (Sigma assessment) | The chosen Azure model meets the task and fits the existing application environment | The chosen Google model meets the task and fits the existing application environment | A tested local model meets a control requirement or supports a justified sustained workload |
| Official sources | Microsoft: Azure hosted-model pricing Microsoft: Azure pricing calculator |
Google Cloud: Hosted-model pricing Google: Google Cloud pricing calculator |
NVIDIA: AI Enterprise standard licensing and pricing |
Compare the same task and service level
Estimate input and output separately. Long documents, repeated context, generated text, retrieval, storage, and additional tools can all affect a cloud application bill. Use the selected provider's current rates; there is no defensible single “cloud AI price.”
For local deployment, NVIDIA's $4,500 reference is a software subscription, not a GPU or server price. Two covered GPUs would represent $9,000 annually at that reference before hardware, electricity, cooling, staffing, and other software. Some hardware or commercial arrangements include entitlements, so check the actual proposal.
Decide with a workload test
Run representative requests and measure useful answers, latency, concurrent capacity, and operating cost. A smaller local model may serve the task well, or it may require more human correction than the hosted model. Equal token counts do not establish equal business outcomes.
Include redundancy and recovery when the application is important. A single local server and a resilient hosted design are not equivalent service levels. Sigma can help compare the model, hardware or cloud services, and implementation as a complete AI project with clearly stated cost assumptions.
Questions to ask before you buy
- What volume of requests do we expect each month, and how steady is it?
- Must data stay on our premises for legal or contractual reasons?
- Who will run GPU servers, updates and security?
- What does the same workload cost per month in the cloud?
What Hawaiʻi businesses should check
On-premises GPU servers in Hawaiʻi add shipping time and higher electricity costs to the budget; include both in the comparison with cloud.
Frequently asked questions
Is it cheaper to run AI on-premises?
Only at steady, high utilization. For occasional or growing workloads, cloud services usually cost less because you pay only for what you use.
Sources and pricing notes
Prices and specifications checked September 27, 2026 against the providers’ published sources below. Prices are US list or published rates before taxes, fees and equipment unless stated; offers change, so confirm the current terms before you buy.
- NVIDIA. AI Enterprise standard licensing and pricing
- Microsoft. Azure hosted-model pricing
- Google Cloud. Hosted-model pricing
- Microsoft. Azure pricing calculator
- Google. Google Cloud pricing calculator
How Sigma is paid. Sigma is a Hawaiʻi technology advisor. Provider or reseller partners compensate Sigma; product and service prices may include a margin. No procurement fee applies. Standalone consulting is quoted separately.