Meta, the owner of Facebook, Instagram, and WhatsApp, is testing its first in-house chip designed for training AI systems, sources told Reuters.

The social media giant has started a limited rollout of the chip, planning to scale up production if testing delivers positive results. The move represents a crucial step in Meta's strategy to lessen dependence on external suppliers like Nvidia and lower substantial infrastructure costs.

The company has projected expenses between$114 billion and$119 billion for 2025, with up to$65 billion dedicated to AI infrastructure.

The chip, part of Meta's Meta Training and Inference Accelerator (MTIA) series, is a dedicated AI accelerator, meaning it is specifically designed for AI tasks rather than general processing. This could make it more power-efficient than traditional GPUs.

Meta is collaborating with Taiwan-based chip manufacturer TSMC to produce the new hardware. The test phase follows Meta's first 'tape-out' of the chip, a crucial milestone in silicon development where an initial design is sent to a chip factory.

However, this process is costly and time-consuming, with no guarantee of success, and any failure would require repeating the tape-out step.

Meta has previously faced setbacks in its custom chip development, including scrapping an earlier version of an inference chip after poor test results. However, the company has since used another MTIA chip for AI-powered recommendations on Facebook and Instagram.

The new training chip aims to first enhance recommendation systems before expanding to generative AI applications like the chatbot Meta AI.

Meta executives hope to implement their own chips for AI training by 2026, although the company continues to be one of Nvidia's biggest customers, investing heavily in GPUs for its AI operations.

The development comes as AI researchers increasingly question whether scaling up large language models by adding more computing power will continue to drive progress. The recent emergence of more efficient AI models, such as those from Chinese startup DeepSeek, has intensified these debates.

While Nvidia remains a dominant force in AI hardware, fluctuating investor confidence and broader market concerns have caused turbulence in the company's stock value.