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Contemporary frontier speech models still catastrophically fail on living Arabic dialects, with top systems like GPT-4o achieving an error rate no better than 35.0% WER across 17 regional vernaculars.
Resource-constrained Arabic AI development can compete with systems built at far greater scale, as demonstrated by Fanar 2.0's performance gains using 8x fewer pre-training tokens than its predecessor.
