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What To Know
- AI has partnered with Stanford University’s Center for Research on Foundation Models, known as CRFM, to launch HELM Arabic, a structured evaluation framework designed specifically for Arabic large language models.
- The HELM Arabic benchmark brings Stanford’s evaluation methodology into the Arabic language space, creating a public leaderboard where models are tested under consistent conditions.
- AI benchmarking has entered a new phase, and the region’s developers are now operating within a transparent evaluation environment.
Arabic.AI benchmarking just got a serious upgrade, and Dubai is right in the middle of it. Arabic.AI has partnered with Stanford University’s Center for Research on Foundation Models, known as CRFM, to launch HELM Arabic, a structured evaluation framework designed specifically for Arabic large language models. For years, Arabic.AI developers worked without a shared public benchmark. Claims about performance floated around, but there was no universal scoreboard. Now there is.
The HELM Arabic benchmark brings Stanford’s evaluation methodology into the Arabic language space, creating a public leaderboard where models are tested under consistent conditions. For founders, researchers, and enterprise teams in Dubai and the wider region, this is a major moment.
What HELM Arabic Actually Means
HELM stands for Holistic Evaluation of Language Models. Developed by Stanford CRFM, the framework evaluates large language models on multiple dimensions, including accuracy, reasoning, bias, and robustness. It has been widely used for English models and is recognized in academic and industry circles.
Arabic, spoken by more than 400 million people worldwide, did not have a dedicated extension of this framework. That gap left regional AI teams without a standardized way to measure performance in Arabic tasks.
HELM Arabic changes that.
The platform introduces structured evaluation tasks tailored to Arabic language understanding and generation. Results are published on a public leaderboard hosted through Stanford’s HELM interface. For startups and enterprise teams, this creates clarity. Instead of relying on internal testing methods, developers can now see how models perform under the same academic framework.
The Leaderboard and LLM X
With the first phase of HELM Arabic live, attention quickly turned to the rankings. According to the published leaderboard, Arabic.AI’s proprietary model LLM X, also referred to as Pronoia, currently ranks at the top across seven evaluation task clusters. The model recorded the highest overall performance in the initial release of results.
Arabic.AI is also listed as the only non open model trained specifically for Arabic language use among the leading entries. While several open weight regional models appear on the board, including AceGPT v2, ALLaM, and earlier versions of Jais, their scores place them below the top tier in this release.
It is important to note that some of these evaluated versions date back to 2024. AI development cycles are fast, and updated iterations may perform differently in future benchmark rounds. Meanwhile, global open source models such as Qwen and Llama have also placed within the top ten, showing strong multilingual performance in Arabic evaluation tasks.
A Statement From Leadership
Nour Al Hassan, CEO of Arabic.AI, stated that Arabic language models have historically received less attention in foundation model research. The collaboration with Stanford CRFM aims to put Arabic.AI evaluation on equal academic footing with English benchmarks.
For Dubai’s growing AI ecosystem, that matters. Standardized benchmarking strengthens trust in local innovation, supports enterprise adoption, and positions regional AI products within global research
conversations. The HELM Arabic benchmark is now live, and the leaderboard is public.
For AI founders in Dubai, this sets a new baseline. Model performance can now be evaluated through a recognized academic framework rather than isolated claims.
Arabic.AI benchmarking has entered a new phase, and the region’s developers are now operating within a transparent evaluation environment. As more models are tested and updated, the leaderboard will continue to evolve. For now, Dubai’s AI scene has a global reference point, and that changes the conversation.
