Mistral AI • LLM
Mistral Saba is a 24B-parameter language model specifically designed for the Middle East and South Asia, delivering accurate and contextually relevant responses while maintaining efficient performance. Trained on curated regional...
Context Window
33K tokens
Input Price/1M
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Output Price/1M
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Parameters
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Mistral: Saba results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| SciCode | 24.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU-Pro | 61.0 | 100.0 | — |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MATH-500 | 67.7 | 100.0 | Artificial Analysis official API |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Intelligence Index | 12.1 | 100.0 | Artificial Analysis official API |
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU Pro | 61.1 | 100.0 | Artificial Analysis official API |
| GPQA Diamond | 42.0 | 100.0 | Artificial Analysis official API |
| HLE | 4.0 | 100.0 | — |
Mistral: Saba is an AI model developed by Mistral AI, classified as a large language model (LLM). It focuses on text processing and natural language generation. As an open source model, it is available for download, customization, and on-premises deployment. With a context window of 33K tokens, it is suitable for processing medium-sized documents like articles, reports, and code sections.
Mistral: Saba does not have public per-token pricing available at this time. Some models offer access via enterprise plans or research programs. Check Mistral AI's official website for up-to-date availability and pricing.
Mistral: Saba was evaluated on 7 different benchmarks, covering categories like Coding, Knowledge, Math, overall, Reasoning. Results show moderate performance across available evaluations.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
Mistral: Saba is suitable for a wide range of AI applications: automation with tool calling (API integration, databases, external systems), text generation, summarization, translation, and general assistance.
In the 2026 AI model ecosystem, Mistral: Saba competes directly with similarly capable models. Mistral AI competes in this segment against OpenAI, Anthropic, Google, and Meta. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
Mistral Saba is a 24B-parameter language model specifically designed for the Middle East and South Asia, delivering accurate and contextually relevant responses while maintaining efficient performance. Trained on curated regional...
Mistral: Saba does not have public per-token pricing available at this time. Check Mistral AI's official website for up-to-date information.
In available benchmarks, Mistral: Saba scored: SciCode: 24/100, MMLU-Pro: 61/100, MATH-500: 67.7/100. See the full table above for a detailed comparison.
Yes, Mistral: Saba is an open source model. You can deploy it on-premises, customize it via fine-tuning, and maintain full control over your data. Check the official repository for the specific license.
Mistral: Saba excels at general-purpose language tasks. It supports tool calling for API integrations and automation.
Last updated: June 01, 2026 • View methodology →