KazLLM, AlemLLM or Foreign Open-Weight Models: How to Choose a Model for a Private Environment
Contents
A closed AI system needs a model that you can deploy on your own infrastructure or in a Kazakhstan cloud. The choice is broader than it may seem: there are Kazakhstan models and dozens of international open-weight models. The right choice depends on your documents, languages, and tasks, not on rankings.
Kazakhstan models
Kazakhstan is developing its own language models. According to published information, these include KazLLM, AlemLLM, and the compact Sherkala, with approximately 70, 246, and 8 billion parameters, respectively. They are designed for Kazakh, Russian, and mixed-language contexts. AlemLLM is reportedly used for practical tasks in a closed government environment.
Check parameters, licenses, and access terms for model weights against primary sources at the time of your project: they change.
International open-weight models
Open-weight models from international developers come in different sizes and perform well in Russian. Their quality in Kazakh varies and requires testing.
Selection criteria
| Criterion | What to check |
|---|---|
| Languages | quality in Kazakh, Russian, and mixed-language text specifically in your documents |
| Terminology | understanding of industry and scientific terms |
| Quality with search | accuracy of answers based on retrieved passages and correctness of citations |
| Speed | response time on your infrastructure |
| Hardware requirements | how much GPU memory is needed for acceptable speed |
| License | whether use is permitted for your scenario |
| Support and updates | who releases new versions and how often |
Several models instead of one
A production system often uses several models:
- a compact model for classification and de-identification;
- a separate model for semantic search;
- a more capable model for complex answers;
- a model for recognizing scans and images.
This approach is cheaper and safer than sending every request to one large model.
Common mistakes
- choosing the largest model just in case and overpaying for hardware;
- choosing based on general rankings without testing on your own documents;
- ignoring the license;
- having no plan for updating the model.
Frequently asked questions
Is a Kazakhstan model required in a government institution?
That depends on the requirements of the specific institution and project. In any case, national models are worth including in the comparison.
Do we need to fine-tune the model on our documents?
Usually not. Document search with answer generation provides up-to-date knowledge without fine-tuning and lets you remove documents.
How often should you change the model?
When a version becomes available that performs better on your benchmark set. The question set itself becomes a tool for making these decisions.
