Meta to Start Manufacturing Own AI Chips in September Amid Component Shortage

In a bid to lower its GPU costs amid an unprecedented component shortage, Meta is on track to start making the latest versions of its AI-specific chip in September, Reuters reported, citing an internal memo.

At least one chip sailed through its testing phase in about six weeks, the memo said. Meta is working with Broadcom on the chip design, however it will use Taiwan’s TSMC to manufacture them. It is also buying RAM from Samsung, storage from Sandisk, and fiber optic equipment from Sumitomo Electric, according to the report.

Meta detailed the four new chips, developed under its Meta Training and Inference Accelerator (MTIA) program, in March, some of which are currently in deployment or will be this year or next. The company is taking a modular approach to designing these chips, anticipating that their needs will change as AI evolves rapidly by the time the chips are in production.

“Each MTIA generation builds on the last, using modular chiplets, incorporating the latest AI workload insights and hardware technologies, and deploying on a shorter cadence,” the company wrote at the time.

The chips are expected to help the company save on buying GPUs from chipmakers like Nvidia and AMD, although it still expects to spend plenty with those providers as well, Reuters reports. Meta intends to use the MTIA chips for training models for its ranking and recommendation algorithms, broader AI workloads, and inference aimed at its applications. The social media company has been producing its own AI chips since 2023.

Meta has been spending massively on securing enough computing capacity to power its various AI efforts. The company in April said it expects capital expenditures between $125 billion and $145 billion this year, a lot of which is going towards its AI efforts.

The company has been striking data center and power deals across the world, spending tens of billions to secure computing capacity to train and deploy its new Muse Spark series of AI models. It plans to deploy 7 gigawatts of compute this year, and double that next, according to Reuters, which cited the memo.

It also signed a deal with ARM last year to secure compute for its recommendation systems, in addition to a multi-billion deal with AMD for its Instinct GPUs, and a multi-billion dollar deal with Amazon to use the cloud giant’s homegrown CPUs for AI-related needs.

Meta isn’t the only company trying to stem the tide of capital going to Nvidia. OpenAI last month unveiled an inference processor that it is building with Broadcom, and Anthropic is said to be considering developing its own chips with Samsung. Amazon and Google both develop their own chips for AI training and inference, and there’s a host of startups building in the space to meet skyrocketing demand.

Meta declined comment.