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[ARTICLE · art-99329] src=arxiv.org ↗ pub= topic=large-language-models verified=true sentiment=↑ positive

Jais 2: A Family of Arabic-Centric Open Large Language Models

MBZUAI, Cerebras, and Inception released Jais 2, a family of Arabic-centric open large language models, including the largest open Arabic-centric LLM trained from scratch at 70B parameters and an 8B-parameter variant. The models achieve leading results on OALL2 and AraGen benchmarks, and are released on HuggingFace under a commercially permissive license, with the 70B model available as a chat app running on Cerebras hardware at up to 2,000 tokens per second.

read1 min views8 publishedAug 17, 2026

arXiv:2608.13580v1 Announce Type: new Abstract: Jais 2 is a family of Arabic-centric large language models developed jointly by MBZUAI, Cerebras, and Inception, designed to advance Arabic-centric language modeling, with strong performance across the Arabic and culturally grounded benchmarks evaluated in this report. The family includes, to our knowledge, the largest open Arabic-centric LLM trained from scratch at 70B parameters, and a competitive 8B-parameter variant among the evaluated open models. A custom Arabic-centric vocabulary enables efficient training and inference. In addition, an optimized architecture and training recipe yield highly compute-efficient training. With a substantially smaller token budget than comparable models, Jais 2 achieves strong Arabic performance on the benchmarks considered in this report and competitive English results. The models obtain leading results among the evaluated open models on OALL2 and AraGen. They also perform strongly on several culturally grounded Arabic benchmarks, including poetry, religion, cuisine, and dream interpretation, as well as in general tasks such as translation and summarization. We release the models in HuggingFace under a commercially permissive license. Jais 2 70B is also released as a chat app on the Web, iOS, and Android; it runs on Cerebras hardware, delivering up to 2,000 tokens per second, and enabling high-throughput Arabic-centric chat serving in our deployment setting. By uniting scale, linguistic diversity, cultural fidelity, openness, and speed, Jais 2 provides an open-weight foundation intended to support further research and development in Arabic-centric LLMs.

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