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Alibaba's aegaeon system reduces nvidia gpu usage by 82% for serving multiple large language models, cutting required gpus from 1,192 to 213 while boosting output by 9x and slashing latency by 97% Alibaba cloud details a gpu pooling system that it claims reduced the number of nvidia h20 required by 82% when serving dozens of llms of up to 72b parameters — the new aegaeon system can serve dozens of large language models using a fraction of the gpus previously required, potentially reshaping ai workloads more Amid us export curbs, this innovation enhances ai efficiency and scalability for cloud providers.

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Alibaba group holding has introduced a computing pooling solution that it said led to an 82 per cent cut in the number of nvidia graphics processing units (gpus) needed to serve its artificial. Alibaba introduces aegaeon, a computing pooling system reducing nvidia gpu reliance by 82%. According to a report from south china morning post, aegaeon allows a single gpu to serve multiple ai models at once, drastically reducing the total hardware needed

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In testing, the system cut the number of nvidia h20 gpus required to serve dozens of models — some with up to 72 billion parameters — from 1,192 to just 213.