Your Own GPU Server or the Cloud in Kazakhstan: How to Calculate the Cost of an AI Platform
Contents
When an organization decides to implement AI in a closed environment, buying a server with GPUs is often the first consideration. This is an expensive decision that is easy to make too early. First, you need to understand the workload, data requirements, and the quality you need to achieve.
Three hosting options
| Option | Upfront costs | Ongoing costs | When it fits |
|---|---|---|---|
| External API | low | based on request volume | public and anonymized data only |
| GPU in a Kazakhstan data center | none or low | monthly rental | personal data, data localization requirements, variable workloads |
| Your own server | high | electricity, hosting, maintenance | sustained high workloads, isolated environment |
Kazakhstan law requires personal data to be stored within the country. For research institutes and other institutions, this makes renting GPU capacity in a Kazakhstan data center a reasonable middle ground between a foreign API and buying equipment.
Rental price benchmarks
Providers in Kazakhstan publish rental prices for servers with GPUs. Public price lists show a wide range, from hundreds of thousands of tenge per month for entry-level configurations to millions of tenge for servers with A100 and H100 class accelerators. Prices depend on the GPU model, memory, storage, service level, and operating schedule, so you should request current prices before making calculations.
Costs beyond the GPU
- servers for document recognition, search, and data preparation;
- document storage and a search index;
- backups;
- monitoring, access management, and logging;
- network connections;
- model updates and operations;
- design, quality evaluation, and protection against data leaks;
- redundancy if the system is critical.
What determines the required computing capacity
- model size and the required quality of responses;
- number of concurrent users;
- context length: how much text the model processes at once;
- acceptable response time;
- volume of documents for initial processing.
The right sequence
- Classify the data and security requirements.
- Run a pilot using an anonymized sample.
- Measure speed, latency, workload, and quality.
- Compare the options based on the three-year cost of ownership.
- Only then select and buy equipment, if needed.
Frequently asked questions
Can you start with a single workstation?
Yes, for a pilot in one laboratory or department. A multiuser system requires server infrastructure.
Which option costs less in the long run?
Under sustained high workloads, your own server can pay for itself. For variable workloads, renting is usually more cost-effective.
What if equipment has to be purchased through public procurement?
Then a pilot is even more important: the procurement technical specification should be based on measurements, not assumptions.
