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Baidu and iQIYI Q2 2026 financial performance

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2026-08-18 23:43 UTC → 2026-08-19 14:07 UTC · added ~~removed~~

Baidu and iQIYI reported second-quarter 2026 financial results that missed analyst expectations. Baidu reported a 4.0% decline in revenue to ¥31.32B, ~~with non-GAAP earnings per share falling 34.7% short of consensus estimates.~~ marking its fifth consecutive quarterly revenue drop. This contraction was largely driven by a 19% annual decline in its core online marketing and advertising division. iQIYI also reported a revenue miss and a wider-than-expected non-GAAP loss of ¥0.13 per share, alongside a 5.0% year-over-year decrease in revenue. ~~Subsequent details regarding~~ Despite the overall revenue decline, Baidu’s ~~performance highlighted a~~ strategic ~~shift~~ pivot toward ~~AI-driven growth. While the online marketing division saw a 19% annual drop in revenue, the~~ artificial intelligence showed significant momentum. The company’s Core AI-powered Business reached RMB 12.5 billion, accounting for 50% of its general business revenue. A major driver was the AI Cloud infrastructure segment, which saw revenue rise 50% year-over-year to RMB 7.3 billion. Specifically, the GPU Cloud division experienced a “283% revenue explosion,” marking its fourth consecutive quarter of triple-digit growth due to demand for AI training and inference computing. ~~Baidu also reported operational progress, including~~ CEO Robin Li stated that the growth in AI reinforces the company’s transition from an “internet-centric model to an AI-first company.” Operational highlights include the international expansion of ~~its~~ the Apollo Go autonomous driving service into Dubai and testing in ~~London. Additionally,~~ London, as well as the ~~company is pursuing~~ company’s ongoing pursuit of a voluntary conversion to a dual-primary listing in Hong Kong, which is expected to become effective within the year. Despite a dip in stock price following the revenue contraction, management emphasized long-term confidence in their full-stack AI capabilities, spanning chips, cloud, models, and applications. Kong.

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