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GEM Training: How Meta Doubled the Efficiency of Its LLM-Scale Ads Foundation Model

Meta's Generative Ads Recommendation Model (GEM), the foundation model behind ads recommendations on Instagram and Facebook, now trains at LLM scale on several thousand of the latest-generation GPUs, achieving a doubling of end-to-end training efficiency to 20–25% Model FLOPs Utilization (MFU) while scaling training FLOPs 4x, as detailed in a post on Engineering at Meta.

read1 min views4 publishedAug 3, 2026

Meta’s Generative Ads Recommendation Model (GEM), the foundation model behind ads recommendations across Instagram and Facebook, now trains at LLM scale on several thousand of the latest-generation GPUs. This post goes into the details on how we achieved: doubling end-to-end (E2E) training efficiency to 20–25% Model FLOPs Utilization (MFU) while scaling training FLOPs 4x in [...]

The post GEM Training: How Meta Doubled the Efficiency of Its LLM-Scale Ads Foundation Model appeared first on Engineering at Meta.

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