Meta Andromeda Achieves 10 Billion Ads Per Second With New Retrieval Architecture
Meta has updated its Andromeda ads retrieval engine to process over 10 billion ads per second on a single GPU, using a new architecture inspired by large language models. The system combines model, system, and hardware co-design to deliver near-ranking-level performance at retrieval scale with significantly fewer computational resources. Advertisers benefit from improved matching accuracy and efficiency, as the system can now handle the expanded ad candidate pool generated by generative AI tools. The update includes a fused GPU kernel that eliminates memory bandwidth bottlenecks and a co-location strategy that reduces network traffic by 100x, shifting the system back to a compute-bound regime.
Meta has updated its Andromeda ads retrieval engine to process over 10 billion ads per second on a single GPU, using a new architecture inspired by large language models. The system combines model, system, and hardware co-design to deliver near-ranking-level performance at retrieval scale with significantly fewer computational resources. Advertisers benefit from improved matching accuracy and efficiency, as the system can now handle the expanded ad candidate pool generated by generative AI tools.
The update includes a fused GPU kernel that eliminates memory bandwidth bottlenecks and a co-location strategy that reduces network traffic by 100x, shifting the system back to a compute-bound regime. This allows for greater model capacity and performance improvements without a proportional increase in GPU costs.
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Source: Meta Engineering · Published 2026-10-28. Reported by Benny Byte.