Deploy a private Azerbaijani LLM
Deploy a private Azerbaijani LLM with Prometheus: a practical, on-prem approach built for Azerbaijani teams.
Deploy a Private, Native Azerbaijani LLM
Most large language models treat Azerbaijani as a secondary consideration, forcing organizations to contend with inefficient tokenization, missing characters, and generic training data that fails to capture linguistic nuance. Prometheus solves this by serving as the first LLM built natively for the Azerbaijani language. Trained on a curated corpus of over 651 million Azerbaijani words and rigorously validated across 11 disciplines using the TUMLU benchmark, Prometheus provides a level of linguistic precision and cultural grounding that general-purpose models cannot match. Beyond linguistic accuracy, Prometheus is engineered for absolute data sovereignty. Unlike cloud-based AI, it is deployed fully on-premise, ensuring that your sensitive organizational data never leaves your internal network. By combining a native tokenizer that masters the ə character and agglutinative morphology with a flexible architecture available in 39B, 99B, and 587B parameter sizes, Prometheus allows your team to implement high-performance AI without compromising security or linguistic integrity.
The Prometheus Advantage for Azerbaijani Enterprises
Complete Data Sovereignty: Full on-premise deployment ensures your data never leaves your network, eliminating external transfer risks.
Native Linguistic Architecture: Purpose-built for Azerbaijani from the ground up, avoiding the limitations of retrofitted multilingual bases.
Superior Processing Efficiency: Achieve 4.6× greater efficiency on Azerbaijani text thanks to a specialized native tokenizer.
Scalable Model Configurations: Match your compute resources to your needs with three parameter sizes: 39B, 99B, or 587B.
Rigorous Domain Validation: Performance is proven via the TUMLU benchmark, covering 38,139 native questions across 11 disciplines.
Morphological Precision: Native handling of the ə character and complex agglutinative structures for higher output quality.
Core Technical Capabilities
Native Azerbaijani Tokenizer
Prometheus uses a tokenizer designed specifically for Azerbaijani, correctly handling the ə character and the language's agglutinative structure. This results in 4.6× greater efficiency on Azerbaijani text compared to models using generic tokenizers.
Three Deployment Sizes
Available in 39B, 99B, and 587B parameter configurations, Prometheus lets your team match model capability to available infrastructure and use-case requirements without overspending on compute.
Fully On-Premise Architecture
The entire model runs within your own network. No API calls to external servers, no cloud dependency, and no risk of sensitive organizational data leaving your environment.
651M+ Words of Curated Training Data
Prometheus was trained on a carefully curated corpus of over 651 million Azerbaijani words, giving it a grounded understanding of the language as it is actually written and used.
TUMLU Benchmark Validation
Performance is measured against TUMLU, a rigorous benchmark of 38,139 native Azerbaijani questions across 11 academic and professional disciplines, providing transparent, domain-specific quality signals.
Deployment Workflow
Frequently Asked Questions
Does Prometheus send any data to external servers during inference?
No. Prometheus is deployed fully on-premise, meaning all processing happens within your own network. Your data never leaves your infrastructure.
Why is a native tokenizer critical for the Azerbaijani language?
Azerbaijani utilizes specific characters like ə and features agglutinative morphology, where complex meanings are built through suffixes. Generic tokenizers often struggle with these, whereas Prometheus's native tokenizer handles them correctly, resulting in 4.6× greater efficiency.
How do I choose between the 39B, 99B, and 587B parameter sizes?
The 39B model is ideal for teams with limited hardware or low-latency needs. The 99B model provides a balance of capability and resource efficiency. The 587B model is designed for organizations requiring maximum linguistic depth and possessing the necessary infrastructure. Allmaz can provide a tailored assessment.
What makes the TUMLU benchmark a reliable measure of quality?
Unlike proxy evaluations or translated tests, TUMLU consists of 38,139 native Azerbaijani questions across 11 distinct disciplines. This provides an objective, domain-specific validation of how the model performs in real-world Azerbaijani contexts.
Can Prometheus be integrated into our existing software ecosystem?
Yes. Prometheus is designed for seamless integration with your internal applications and workflows via standard APIs, allowing you to embed native Azerbaijani AI capabilities directly into your current tools.
Secure Your Private Azerbaijani LLM
Talk to the Allmaz team about deploying Prometheus in your environment. We will help you choose the right model size, plan your infrastructure, and get your team working with a language model that genuinely understands Azerbaijani.
Request a demo