Meta Q3 Revenue Jumps 26% as AI Costs Mount

Meta third-quarter revenue rose 26% year on year to $64.6 billion, beating estimates, while its fourth-quarter forecast also topped expectations. Advertising revenue climbed 26% to $63.06 billion, nearly 98% of sales, as ad impressions rose 10% and average prices increased 14%. Meta said AI tools and recommendation systems are helping improve ad performance. Meta’s AI spending is also weighing on cash flow. Capital spending and finance lease principal payments reached $34.91 billion, above operating cash flow of $32.79 billion, leaving free cash flow at negative $2.12 billion. The company set its FY2026 capital expenditure outlook at $135 billion–$145 billion and said investment would remain aggressive in 2027. Its fourth-quarter revenue forecast of $73 billion–$76 billion was above market expectations at the midpoint. Meta’s AI assistant Muse drew more than 10 million accounts in the US and Canada in about six weeks, with roughly one in four users active on a typical day. The company expects to improve Muse’s cost efficiency more than tenfold over the next year, but it has yet to establish a proven revenue model. Shopping, subscriptions and developer services are potential monetisation routes. Meta is also seeking to reduce Reality Labs losses, has cut jobs and plans to issue non-voting Class C shares, allowing financing and stock compensation flexibility without changing voting control. Shares rose about 2.9% in after-hours trading. For crypto traders, the report has no direct token catalyst; it is chiefly a signal about AI-sector investment, corporate cash flow and broader risk sentiment.
Neutral
Meta is not a cryptocurrency, and neither summary identifies a specific crypto asset whose price could be directly affected. The earnings report may influence broad risk appetite: strong revenue and advertising growth could support sentiment toward AI and technology, while negative free cash flow and sharply higher capital spending highlight execution and financing risks. These signals may contribute to short-term volatility in crypto markets through broader risk-on or risk-off trading, but they do not establish a directional catalyst for any individual token. Over the longer term, the report may shape views on AI investment and corporate spending, yet its impact on crypto prices remains indirect and uncertain. A neutral classification is therefore appropriate.