Fast Food Beats Luxury in China's AI Search: The 2026 GEO Category Benchmark

If you assumed the brands with the biggest marketing budgets would dominate China's AI assistants, the data says otherwise. Averaging hubGEO's brand visibility scores across every tracked brand in each sector, fast food chains post the highest category average of any industry we cover — 79.0 out of 100 across Doubao, Kimi, DeepSeek, Qwen, Wenxin, and Hunyuan. Luxury houses, despite decades of nine-figure marketing spend, average 75.7. Beauty brands, one of the most heavily advertised categories in China, come in dead last at 55.8. Product prestige and AI citation frequency are not the same thing, and the gap between them is where most GEO strategy mistakes happen.

This matters more in mid-2026 than it did a year ago. Doubao crossed roughly 260 million monthly active users this spring after overtaking Baidu, DeepSeek has climbed past 180 million MAU and is now being tested inside WeChat's own search bar, and Kimi's user base has fallen below 10 million as it slides out of the top tier of consumer AI apps. The six-model landscape brands need to optimize for keeps consolidating around a smaller set of dominant, high-traffic assistants — which makes knowing your category's realistic ceiling and floor more useful than ever.

The category scoreboard

These averages come from hubGEO's ongoing brand audit, which runs twelve queries per brand across all six models and refreshes monthly, so the figures reflect a live snapshot rather than a one-off estimate.

Why fast food wins: universality beats prestige

Fast food's advantage has nothing to do with sophistication and everything to do with volume and consensus. KFC (94.0) and McDonald's (92.0) generate enormous, constantly refreshed Mandarin-language content: Meituan and Ele.me delivery reviews, Dianping ratings, menu-price comparison threads, franchise news, and nutrition breakdowns. Every one of China's AI models trains on some version of this content, and none of it requires interpretation — a fried chicken combo is described identically in every review, every city, every model. There's no ambiguity for the AI to resolve, so citation is nearly automatic. Subway is the exception that proves the rule: its 40.0 average, roughly half of KFC's, tracks a much thinner Chinese delivery-platform footprint and a store count that has shrunk in recent years, which starves the same content pipeline that lifts its QSR peers.

Luxury brands post a respectable average (75.7) for a very different reason: heritage rather than volume. Louis Vuitton, Chanel, and Gucci have accumulated four decades of Mandarin editorial coverage, celebrity endorsement history, and counterfeit-goods reporting that keeps them in circulation across unrelated query types — economic commentary, social-status narratives, resale-market coverage. But that advantage is unevenly distributed within the category, which is where luxury's story gets more interesting than its headline average suggests.

The real story is the spread, not the average

A category average hides how differently brands within it actually perform. Measuring the point gap between each category's top and bottom scorer:

Beauty has the lowest category average and the widest internal spread in our entire database — a 76-point gap between Lancôme (92 Doubao / 88 Kimi / 90 DeepSeek / 94 Qwen / 86 Wenxin / 89 Hunyuan, averaging 89.8) and Drunk Elephant (14 / 12 / 16 / 18 / 10 / 13, averaging 13.8). That is a wider gap than luxury's supposedly more rarefied hierarchy, where Louis Vuitton (93/90/92/94/88/91, avg 91.3) still outscores Tiffany & Co. (45/40/48/42/38/44, avg 42.8) by "only" 48.5 points.

The pattern: beauty is the most winner-take-all category we track. Legacy dermatologist-and-department-store brands (Lancôme, Estée Lauder, L'Oréal) that have spent decades building clinical and editorial content in Mandarin sit near 85-90. Younger, DTC-native brands (Drunk Elephant, Charlotte Tilbury) that built their reputations primarily through Western Instagram and TikTok content have almost no equivalent footprint in the Chinese-language sources these six models actually draw from, and it shows up as a near-total AI blackout rather than a modest gap.

A cross-category mid-tier cluster worth noticing

One of the more striking patterns in the full dataset is that several brands from entirely different industries land in almost the same narrow band, in the high 30s: Volvo (auto, 39.8), Bose (electronics, 36.3), and Lululemon (sports, 36.8). These are all respected, recognizable, premium-positioned Western brands — none of them budget or unknown. What they share isn't sector, it's structure: each competes in a narrow product vertical (safety-focused wagons and SUVs; headphones and speakers; yoga and athleisure apparel) with limited crossover into adjacent content categories, and a Chinese-language presence that leans heavily on transactional Tmall and JD listings rather than the multi-vertical editorial footprint that lifts brands like Sony (electronics, 75.3) or BMW (auto, 89.7). Category doesn't determine this outcome — content breadth does, and its absence produces nearly identical results whether the product is a wagon, a woofer, or a pair of leggings.

The models don't grade on the same curve

Averaged across all 39 brands in the database, the six models are not equally generous graders: DeepSeek averages 70.4, Qwen 69.3, Doubao 68.7, Hunyuan 67.1, Kimi 65.4, and Wenxin comes in lowest at 64.5. The gap between the most and least generous model is only about six points — modest compared to the 76-point spread within the beauty category — but it is consistent enough across brands to matter for prioritization. Wenxin's lower average tracks with Baidu's search-engine heritage: the model leans on indexed web-authority signals more than the other five, which rewards brands with deep, long-running editorial coverage and penalizes those whose Chinese content is mostly recent or transactional. DeepSeek's position at the top, combined with its rapid MAU growth and new WeChat search placement, makes it arguably the single highest-leverage model for brands deciding where to concentrate limited GEO content budget in the second half of 2026.

Luxury's real advantage: a high floor, not just a high ceiling

Category floors turn out to be just as telling as category ceilings. Comparing the weakest performer in each category — Tiffany & Co. (42.8) in luxury, Subway (40.0) in food, Volvo (39.8) in auto, Lululemon (36.8) in sports, Bose (36.3) in electronics, and Drunk Elephant (13.8) in beauty — luxury's floor sits above every category except food, and well above beauty's by a factor of three. Even Tiffany, widely seen as underperforming its own category, still outscores the weakest brand in sports, electronics, and auto. That's the part of luxury's reputation for AI visibility that the "LV and Chanel hit 90+" headlines miss: the category's floor is high because near-universal counterfeit coverage, resale-market commentary, and decades of consumer-aspiration journalism lift even its laggards. Beauty offers no such safety net — fall behind on clinical and editorial content there, and a brand can land in the low teens with almost nothing to catch it.

Takeaway for brand marketers

Don't benchmark your GEO score against your industry's average — benchmark against your industry's spread. A beauty brand sitting at 50 isn't "middling for the category," it's on the wrong side of the widest gap in the entire dataset, and closing it requires the kind of clinical, editorial, dermatologist-authored Mandarin content that legacy beauty houses have spent decades accumulating, not another product-listing translation. Conversely, a fast-food or QSR brand starting a China GEO push inherits a naturally high floor simply because delivery-platform review volume does most of the work — the ceiling there is less about content strategy and more about menu localization and store footprint. Know which kind of category you're in, and which model currently grades hardest, before deciding how much your content team actually needs to produce to move the number.

Related: explore the full brand visibility index for model-by-model scores across all tracked categories.