Meta plans to extend its self-developed chips to AI model training.

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Meta plans to develop custom chips to train its artificial intelligence models.

On Wednesday, March 4, Meta’s Chief Financial Officer Susan Li stated at a technology industry conference hosted by Morgan Stanley, the company remains ambitious in developing its own custom chips, including plans to develop processors capable of training future AI models.

Susan Li said Meta's self-developed chips are currently mainly deployed for ranking and recommendation workloads, she explained:

But we expect and hope to expand this scope over time, eventually including AI model training.

Meta positions itself as one of the hyperscale operators of data centers used for training and operating AI models, even though the company itself is not a cloud services provider.

In the weeks prior, Meta had successively reached large-scale procurement agreements with chip market leader Nvidia and its competitor AMD, to secure supply of chips and equipment needed for AI workloads.

Susan Li emphasized that Meta adopts a differentiated chip procurement strategy, selecting the most suitable processors based on different application scenarios. She said:

Based on information we currently possess and current needs, which chip do we think is most suitable for each application scenario? Custom chips are a critical part of this.

Analysis suggests that Meta is not aiming to replace external chip purchases with in-house development, but rather to build a hybrid supply system. External procurement fulfills current large-scale needs, while self-developed chips are optimized for highly customized internal workloads, enhancing efficiency and controlling long-term costs.

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