# Meta's New AI Chips Enter Production in September, Reducing GPU Dependence

> Meta's in-house AI silicon is moving from the lab toward the factory. The company's MTIA line, short for Meta Training and Inference Accelerator, is set to begin production in September, with at least one chip reportedly completing testing in just six weeks. The design is modular, meant to evolve as Meta's AI workloads change rather than being frozen on day one. The motivation is cost and control. Training and running large models on Nvidia and AMD GPUs is enormously expensive, and every hyperscaler is racing to build its own chips to reduce that dependence. Meta is not going it alone: the effort leans on Broadcom for design, TSMC for manufacturing, and Samsung, SanDisk and Sumitomo Electric for components. Custom silicon is a long game, and Meta will still buy plenty of GPUs for years. But the strategic logic is hard to argue with. Owning more of the stack means better margins, fewer supply bottlenecks, and hardware tuned to exactly the models you run. It is the same vertical-integration playbook that reshaped smartphones, now playing out in the data center.

_Section: [Daily AI Updates](https://www.wortins.com/daily-ai) · Source: TechCrunch · Published Friday, July 10, 2026_

## Wortins' read

Meta's in-house AI silicon is moving from the lab toward the factory. The company's MTIA line, short for Meta Training and Inference Accelerator, is set to begin production in September, with at least one chip reportedly completing testing in just six weeks. The design is modular, meant to evolve as Meta's AI workloads change rather than being frozen on day one. The motivation is cost and control. Training and running large models on Nvidia and AMD GPUs is enormously expensive, and every hyperscaler is racing to build its own chips to reduce that dependence. Meta is not going it alone: the effort leans on Broadcom for design, TSMC for manufacturing, and Samsung, SanDisk and Sumitomo Electric for components. Custom silicon is a long game, and Meta will still buy plenty of GPUs for years. But the strategic logic is hard to argue with. Owning more of the stack means better margins, fewer supply bottlenecks, and hardware tuned to exactly the models you run. It is the same vertical-integration playbook that reshaped smartphones, now playing out in the data center.

## Source

[Read the full story at TechCrunch](https://techcrunch.com/2026/07/09/metas-new-ai-chips-will-begin-production-in-september/)

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