Two of the world’s largest technology companies are under fresh scrutiny over their aggressive artificial intelligence infrastructure spending, with analysts pointing to potential new revenue streams and efficiency gains that could reshape investor sentiment.
Meta Platforms could turn a portion of its expanding data-center footprint into a meaningful external business, according to Evercore ISI. The company is targeting 14 gigawatts of total compute capacity by 2027, and analyst Mark Mahaney argued that Meta is a rare potential seller of surplus capacity in a market where most scaled operators are sold out.
Mahaney raised his price target to $860 from $820, implying more than 50% upside from roughly $570. He estimated that placing just 0.5 to 1 gigawatt of surplus capacity on the market could generate between $11 billion and $22 billion in annual external revenue. Leasing 1 gigawatt would be only about 7% of Meta’s 2027 capacity target while potentially adding as much as $4.32 to earnings per share.
Meta is the only major hyperscaler without a public cloud business, but reports have suggested it could establish a Meta Compute division. Chief Executive Mark Zuckerberg said during the latest earnings call that Meta has received premium offers for computing capacity, but he cautioned that selling all of the compute for short-term profit would be ‘foolish’ because selling intelligence carries a significantly higher margin. Mahaney described the potential compute business as a call option rather than an established annuity stream.
Meanwhile, Alibaba unveiled Qwen3.8-Flash, a lower-cost multimodal AI model aimed at coding and office tasks, as it completed an HK$80 billion, or $10.2 billion, share placement to finance AI expansion. The company’s shares plunged 8.5% on Monday after the offering was announced before recovering 1.5% to HK$114.20 on Tuesday.
Alibaba’s June-quarter results show why efficiency matters. Net profit fell 75% year over year while capital expenditure jumped 75% to 67.68 billion yuan. AI Cloud and Compute Services revenue rose 45% to 48.44 billion yuan, and AI-related products delivered triple-digit growth for a twelfth consecutive quarter. The company said its Qwen family has surpassed 3 billion global downloads and generated more than 300,000 derivative models.
Daiwa analyst John Choi expects losses at Alibaba’s AI Labs and Applications business to decline sequentially, helped by better model training efficiency, improved inference efficiency and lower marketing intensity. Daiwa maintained a Buy recommendation and raised its US ADR target to $185 from $180. Citi analyst Alicia Yap argued that long-term AI success will require enormous resources and a loyal customer base, favoring companies that span chips, cloud infrastructure, models and applications.
BofA warned that the placement could initially weigh on sentiment because of dilution, higher depreciation, uncertain elevated capex and possible additional financing, but it maintained a Buy rating and $172 target. CGS International also retained Buy while cutting its Hong Kong target to HK$185 from HK$209.
