Falcon-H1 Arabic was trained on Arabic-first datasets covering formal language, regional dialects, and culturally grounded content
Abu Dhabi has built an artificial intelligence system that understands Arabic better than any other model on global benchmarks — and it does so while being smaller and faster than competing systems from major tech companies.
Falcon-H1 Arabic, developed by the Technology Innovation Institute (TII), ranks first on the Open Arabic LLM Leaderboard, which measures how well AI systems handle the Arabic language. The flagship 34-billion-parameter model outperforms Meta’s Llama-70B and China’s Qwen-72B, despite being less than half their size.
For Arabic speakers, the impact is practical. Anyone who has tried popular AI tools in Arabic knows the gap: replies that sound grammatical but miss meaning, tools that fail with dialect, or translations that ignore cultural context. Falcon-H1 Arabic was built specifically to eliminate this problem.
Arabic remains one of the hardest languages for AI to model. Words change function based on subtle shifts, word order is flexible, and everyday life involves switching between dialects and Modern Standard Arabic. Global systems trained mainly on English often struggle with this.
Research in Communications of the ACM notes that Arabic lacks large, high-quality annotated datasets — especially for dialects and informal speech — leaving most AI systems undertrained for real usage. The result shows up daily in education, customer service, government services, and healthcare chatbots that perform worse in Arabic than English.
Falcon-H1 Arabic was trained on Arabic-first datasets covering formal language, regional dialects, and culturally grounded content. The model comes in three sizes — 3B, 7B, and 34B parameters — allowing organisations to choose based on their computing resources.
The smallest model (3B) outperforms Microsoft’s Phi-4 Mini by 10 percentage points on Arabic benchmarks. The 7B version leads its category. The largest 34B model surpasses systems more than twice its size, achieving 75.36 percent accuracy on comprehensive Arabic understanding tests.
Beyond performance scores, the model handles tasks that matter in daily life: understanding dialect phrases, reasoning in Arabic, maintaining long conversations, and interpreting context rather than translating word-by-word. It can process up to 192,000 words in a single conversation — enough to analyse legal contracts, academic research or full medical records without losing track of context.
Faisal Al Bannai, Adviser to the UAE President and Secretary-General of the Advanced Technology Research Council, said the achievement enables Arabic-speaking communities to benefit from “innovation that is accessible, relevant, and impactful.”
Arabic is spoken by more than 450 million people across over 20 countries, yet historically has been secondary in global AI development. Many major systems “support” Arabic only as an add-on to English-trained models. Falcon-H1 Arabic was designed from the ground up with Arabic at the centre of development.
The implications extend across multiple sectors in the UAE and wider region. Schools can deploy AI tutors that actually understand students’ language and dialect. Healthcare providers can use AI tools that respect cultural context. Businesses can automate customer support without losing cultural nuance. Government services can operate chat systems in natural Arabic rather than translated English phrasing.
TII’s Falcon models have consistently ranked first in their categories since 2023. The H1 Arabic release continues that trajectory while filling a longstanding gap: an AI foundation model built specifically for Arabic speakers rather than adapted from English.
Falcon-H1 Arabic is freely available at chat.falconllm.tii.ae, allowing developers, startups, researchers, media organisations and public-sector institutions to build Arabic AI applications that work as fluently in Arabic as mainstream tools do in English.