Meta Platforms stock rebounded strongly on Friday as investors welcomed fresh details about the company’s artificial intelligence revenue strategy, data center investments, and competitive model pricing. Shares climbed approximately 6% on the day and posted a nearly 15% weekly gain—the best weekly performance since early 2024.
The rally erased Meta’s year-to-date losses. The stock had been under pressure due to concerns over rising capital expenditure and slower-than-expected returns from AI investments. The latest updates provided Wall Street with clearer signals on how Meta intends to convert its heavy infrastructure spending into new revenue streams beyond advertising.
Meta Explores AI Cloud Business
CEO Mark Zuckerberg revealed that Meta is considering renting AI computing power to external customers, noting that demand for the company’s compute capacity is “so high that it may make sense” to offer access through a cloud business. While the plan remains in early stages, it could involve providing access to AI chips and servers or hosting models for enterprises that need additional computing power. This move would position Meta in direct competition with Amazon Web Services, Microsoft Azure, and Google Cloud.
Demand for computing capacity is rising as users adopt chatbots, coding tools, and agentic systems. Meta already invests heavily in data centers to support Facebook, Instagram, advertising, and AI tools. A cloud offering could generate revenue from the same infrastructure that supports its core platforms.
Muse Spark 1.1 Introduces Paid Model Access
Meta released Muse Spark 1.1, a new AI model optimized for coding and agentic workloads, and introduced pricing for developer access. The company will charge $1.25 per million input tokens and $4.25 per million output tokens—significantly lower than Anthropic’s Claude Opus 4.8, which costs $5 per million input tokens and $25 per million output tokens. This aggressive pricing may appeal to developers seeking cost-effective tools for coding, workflow automation, and AI agents.
Tokens are units of text processed by AI models. Input tokens cover user prompts and commands, while output tokens cover the model’s responses. Lower token prices help developers manage costs when applications handle large volumes of text.
Earlier in the week, Meta also launched Muse Image, an image generation model targeting creators, advertisers, and subscription products. Together, Muse Image and Muse Spark 1.1 demonstrate Meta’s expanding portfolio of AI tools for both business users and developers.
Data Centers and Custom Chips Shape the Spending Debate
Meta announced a new data center in Alberta, Canada, as part of its global infrastructure build-out. The facility will support the company’s growing needs for AI training and model delivery.
Meanwhile, Meta is advancing its custom AI chip, Iris, with production expected to begin in September. Iris is part of Meta’s effort to reduce costs and gain greater control over the hardware powering its AI systems.
Capital spending remains a key investor concern. Meta previously guided 2026 capital expenditure as high as $145 billion, raising questions about the pace at which AI investments will generate returns. However, Bank of America analyst Justin Post noted that Meta “may have engineered significant cost savings” in data center capacity, supporting the view that the company could manage its AI build-out at a lower cost than anticipated.
These developments—combined with AI cloud services, competitive model pricing, infrastructure expansion, and custom chip progress—have renewed investor confidence in Meta’s ability to turn its AI strategy into tangible revenue growth.
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