Mistral's new AI model specializes in Arabic and related languages

Paris-based AI startup Mistral is focusing on providing large language models (LLMs) that understand regional-specific languages and are tailored to grasp the cultural nuances sometimes overlooked in larger, more general-purpose models trained to be versed in multiple languages. 

Mistral has released its first “specialized” regional language-focused model, Saba. According to Mistral, the 24-billion-parameter model has been trained on “meticulously curated datasets” from across the Middle East and South Asia to meet a growing customer base in Arabic-speaking countries. 

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The startup, co-founded by former Meta employees, is attempting to compete with the likes of ChatGPT and Microsoft Copilot with its own AI chatbot — Le Chat. Mistral has developed and released several LLMs, both commercial and open source, that are accessible through websites, mobile apps, and APIs for third-party applications.

Saba is relatively similar in size to Mistral Small 3, an open-source, general-purpose model comparable to larger models such as Llama 3.3 70B, Qwen 32B, and even GPT4o-mini. However, according to Mistral’s metrics, Saba performs better at handling Arabic content than Mistral Small 3 and other LLMs.

The model also excels with South Indian languages like Tamil and Malayalam, according to Mistral, because of “cultural cross-pollination” between the Middle East and South Asia.

Other AI companies are pursuing similar objectives with regional-specific LLMs: OpenAI has developed a Japanese-specific GPT-4 model; the EuroLingua GPT project focuses on European languages; BAAI Beijing open-sourced its Arabic Language Model (ALM) back in 2022; and Nigerian-based Awarri is building its own LLM for low-resource Nigerian languages. 

According to Mistral’s benchmark tests, Saba outperforms Arabic-centric models such as JAIS 70B, and multilingual LLMs such as Mistral Small 3, Llama 3.1 70B, GPT 4o-mini. 

Furthermore, Mistral notes, “Saba provides more accurate and relevant responses than models over 5 times its size while being significantly faster and lower cost. The model can also be a strong base to train highly specific regional adaptations.” Because the model is better at understanding locally-rooted cultural subtleties and the nuances of the Middle East, Mistral argues, it’s more effective for generating region-specific content and ideal for specialized use cases. 

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Saba is available now for conversational support or content generation in Arabic but, according to the company, can also be “fine-tuned” to power Arabic-language virtual assistants for enterprises or “specialized tools [within] the energy, financial markets, and healthcare” sectors. 

The blogpost also states that Mistral Saba is available through Mistral’s API, and can also “be deployed within the security premises of customers.”