Meta Platforms Inc. (NASDAQ: META) shares climbed on Thursday, reversing earlier losses as investors reacted to the company's latest artificial intelligence initiatives, including plans to begin manufacturing its own AI chip and the public preview of an upgraded AI model.
The moves underscore Meta's strategy to strengthen its AI infrastructure, reduce dependence on third-party chip suppliers, and expand its portfolio of proprietary AI products amid intensifying competition from OpenAI, Anthropic, and Google.
Custom AI Chip Strategy Advances
According to an internal memo reviewed by Reuters, Meta plans to start production of its in-house AI chip, code-named Iris, in September. The chip is part of the company's multi-generation Meta Training and Inference Accelerators (MTIA) program, designed to power AI systems behind Facebook and Instagram.
Reuters reported that testing of the chip took only six weeks and revealed no major issues, marking a milestone for an initiative that has faced hurdles since its inception over five years ago. Meta is collaborating with Broadcom on chip design, while Taiwan Semiconductor Manufacturing Co. (TSMC) will handle manufacturing.
The custom silicon is intended to complement the large volume of graphics processing units (GPUs) Meta purchases from Nvidia and Advanced Micro Devices (AMD), while helping the company lower computing costs and reduce reliance on external suppliers. Meta plans to deploy seven gigawatts of computing infrastructure this year, doubling to 14 gigawatts by 2027.
To support its AI expansion, Meta has secured long-term supply agreements with Samsung Electronics for memory chips, Sandisk for flash storage, and Sumitomo Electric for fiber-optic equipment. This vertical integration push comes as the broader chip sector faces valuation concerns, as seen in the recent KOSPI plunge driven by AI valuation fears.
Muse Spark 1.1 Expands AI Ambitions
Alongside its infrastructure investments, Meta introduced Muse Spark 1.1, the latest version of its AI model focused on coding and agentic AI capabilities. The company is offering the model through a public developer preview, with developers able to join a waitlist for API access via Meta's developer portal.
"This is going to be served on top of the computer infrastructure that we’ve built," said Meta's AI chief Alexandr Wang. He described the updated model as Meta's "strongest model for agentic and coding work yet." Wang also noted that the pricing is "very aggressive and attractive" compared with competing offerings from OpenAI and Anthropic. New API users will receive $20 in free credits before usage-based pricing begins.
"The goal is to really have attractive pricing that scales with immense consumption usage," Wang said. According to Wang, Meta trained Muse Spark 1.1 to strengthen coding capabilities because "You kind of have to build coding capabilities as part of that in service of overall agentic capabilities." Meta is currently limiting API access to its own ecosystem rather than making the model available through third-party AI marketplaces.
AI Investments Continue to Expand
The latest announcements come as Meta continues to increase spending on AI infrastructure. Reuters reported that the company expects to spend as much as $145 billion on AI infrastructure this year, accounting for a significant share of Big Tech's projected AI investment. The company also announced plans to build its first Canadian data center in Sturgeon County, Alberta. The AI-optimized facility represents an investment of more than CAD $13 billion, is expected to support about 3,000 construction jobs at peak and more than 300 operational positions, and will run on 100% clean and renewable energy.
Meta's push into custom chips and proprietary AI models reflects a broader industry trend toward vertical integration, as companies seek to control costs and differentiate their offerings. However, the heavy spending on AI infrastructure also raises questions about returns on investment, especially as competition heats up. For context, other tech giants like Adobe face bearish calls on AI competition risks, highlighting the challenges in the AI landscape.
As Meta advances its AI strategy, investors will be watching for signs of tangible revenue growth from these initiatives. The company's ability to scale its custom chip production and attract developers to its Muse Spark platform will be key metrics to monitor in the coming quarters.
This article is for informational purposes only and does not constitute financial advice.
