Meta Andromeda: Powering the Next Generation of Ads Retrieval Through Model-System Co-Design

From the source

The next generation of Meta Andromeda, Meta’s personalized ads retrieval engine, and how co-designing the model, system, and GPU hardware unlocks a new efficiency frontier for ads retrieval. In production, the system scores every eligible ad with near ranking-level model performance at retrieval scale and surfaces the top candidates at over one billion ads per second, a new throughput benchmark for ads retrieval-stage models (i.e., a 100x lift compared to the 2024 Meta Andromeda system).

For advertisers, this means better performance automatically from the retrieval system matching ads across a larger candidate pool, within the same latency budget. Since 2025, Meta Andromeda has delivered a 2.4% increase in conversions on Facebook.

Meta Andromeda is Meta’s machine learning system for personalized ads retrieval, the first stage of the ads recommendation pipeline. Retrieval narrows a vast pool of eligible ads down to a small set of strong candidates in milliseconds; a later, more computationally expensive ranking stage then scores those survivors in fine detail. Historically, the deep modeling quality of the ranking stage has been too costly to apply at retrieval’s scale. …

engineering.fb.com