Golden Week 2026: What China's Six AI Models Recommend for the 13-Day Holiday — and Why Only One International Brand Made the Cut

This year's Mid-Autumn Festival (September 25) and National Day holiday (October 1–7) are only three working days apart. Take September 28–30 off and you get a 13-day break, and Chinese travelers have noticed. Tongcheng Travel data reported in mid-September showed advance hotel bookings in popular cities up nearly 40% year on year. More than 8.58 million domestic air tickets had been booked by September 14, up over 10%. Searches for "Mid-Autumn" and "National Day" were up 278% month on month.

A growing share of those trips starts with an AI prompt, not a search box. On September 16, Jinkoubei Network's AI research unit put one question to China's six mainstream assistants: "Predict the most popular scenic spots for this year's National Day holiday." The six were Doubao, Qwen, DeepSeek, Tencent Yuanbao, Kimi and Baidu Wenxin. The answers make a useful stress test for any travel, hospitality or consumer brand planning its GEO for China.

The headline finding: four of the six models named the Forbidden City as the top pick. Across all six answers, the only international brand named was Shanghai Disney Resort, and it came up in just two of them.

The Six Answers, Side by Side

Source: Jinkoubei Network AI Research Institute test, published via Sohu/Bandao, September 16, 2026.

Finding 1: The Consensus Layer Is Very Narrow

On the head question, the models mostly agree. The Forbidden City, the Terracotta Army, West Lake and Hongyadong appear in almost every answer. That fits what hubGEO sees across categories in its brand tracking. When a query is broad ("most popular," "best," "top"), the six models fall back on the same small set of heavily documented entities. Differences between models only show up further down the list.

For brands, this means that getting into the top slot on a generic query is mostly settled before GEO begins. The Forbidden City gets there on centuries of documentation, not optimization. International brands have a better shot in the second tier: the "dark horse," "hidden gem" and themed sub-lists where each model uses its own logic. Qwen's "hidden-gem towns," Yuanbao's "autumn dark horses" and DeepSeek's poetry theme are the parts of each answer where rankings can still change.

Finding 2: Each Model Cites Its Own Ecosystem

The data-source column tells the most. Qwen cited Fliggy, Alibaba's own travel platform. Wenxin cited Meituan and a public-opinion monitoring service. Yuanbao produced "expert mode" itinerary cards that week, which Tencent was promoting on Weibo. Earlier in the year, Xiaohongshu's own AI assistant, Diandian, added a guide mode that generates routes with map components and one-tap navigation.

This matches the pattern hubGEO has tracked since June: a Chinese AI assistant draws most heavily on the commerce and content ecosystem it belongs to. For travel brands, the practical result is:

• Qwen visibility tracks your Fliggy footprint: listings, reviews and booking volume on Alibaba's OTA.
• Wenxin visibility is shaped by Meituan and Baidu-indexed sentiment data.
• Doubao visibility is shaped by Douyin content, which is why its answers read like a travel vlogger's.
• Yuanbao has WeChat's content supply behind it: Official Account articles and Mini Program data.

An international hotel group or airline that manages only its Ctrip/Trip.com presence, or only its English-language site, covers at most one of these four data sources.

Finding 3: Attractions Get Named, Hospitality Brands Don't

None of the six answers named a hotel chain, an airline or a car-rental brand, and the question never asked for one. That silence is still worth noting. On a trip-planning prompt, the AI's first move is to pick destinations, and destinations then narrow the brand choices. Once a user has settled on "Luoyang for the Longmen Grottoes," the follow-up prompts ("where to stay near Longmen," "fastest way from Beijing to Luoyang") are the ones where hotel and transport brands compete. If a brand is weak in that destination's content cluster, it never gets considered.

That leaves international hospitality brands exposed in 2026's version of Golden Week. Qwen and DeepSeek both pushed "reverse tourism": lower-tier cities and county-level destinations, with DeepSeek citing 42% booking growth in that segment. Global hotel groups usually have their thinnest Chinese-language coverage in exactly those places. Meanwhile, cross-border demand is picking up. Chinanews reported on September 17 that inbound air bookings for the holiday were up about 6% year on year, and outbound long-haul packages were reported up 62% month on month, with visa-free destinations seeing roughly a threefold jump. Brands that serve outbound Chinese travelers face the same models making destination-first decisions.

Shanghai Disney shows what works. It appeared in the Kimi and Wenxin answers not because of a Golden Week campaign, but because it is described consistently as a destination in OTA reports, rankings and news coverage. For most international brands, the lesson is to get covered as part of the destination, not as a supplier to it.

Finding 4: The Evidence Layer Is Being Mass-Produced

The most worrying data point this season has nothing to do with the models. On September 21, Economic Herald reported on an "AI content base" in Caoxian County, Shandong, where more than 30 staff have spent the past two months mostly fulfilling travel-guide orders. One shopping platform reportedly orders about 100,000 keyword groups a week, and a set of AI-generated image-and-text posts sells wholesale for just over ten yuan. An SMZDM analysis published September 22 summed it up: many of the Golden Week guides users save on Xiaohongshu were likely produced by this kind of pipeline, not written by travelers.

That creates a feedback loop brand marketers need to understand:

1. Factory-produced guides flood Xiaohongshu and similar platforms with generic "top 10" lists.
2. AI models that retrieve from those platforms treat the volume as consensus.
3. Model answers get reposted as more guide content, which strengthens the same short list.

Two things follow. First, mass-produced content favors whatever is already popular. The factories write about the Forbidden City and West Lake because those keywords sell, which makes the consensus layer even harder to break into. Second, errors spread. SMZDM collected user reports of AI guides getting ticket prices, reservation rules and seasonal opening dates wrong, including one case where an AI said a tea park was free and it wasn't. As hubGEO noted in our price-hallucination analysis, outdated facts cost more in travel than in almost any other category because users act on them the same day.

For brands this leads to a clear conclusion. Buying more volume on this crowded content layer is a poor bet. We have also covered how low-authority sources are being down-weighted. Investing in authoritative, current, structured facts is a better one: official WeChat accounts, OTA listings with correct opening hours and prices, and coverage in the platform reports the models already quote.

What Users Actually Trust AI For

User behavior this season sets clear limits on how far AI influence goes. SMZDM's roundup of hundreds of user posts found that satisfied users mostly use AI for three things:

• Enumeration and first-pass filtering ("list every kid-friendly spot with a sightseeing shuttle")
• Multi-constraint scheduling (families, elderly travelers, group trips)
• Formatting outputs (itinerary tables, packing lists, shareable cards)

Users say they verify prices, reservations and opening hours on official channels. One heavy Doubao user said a family itinerary took "four hours of repeated prompting." For brands, this splits the funnel. The AI decides the shortlist; official channels decide whether the booking goes through. A brand has to be on the AI's shortlist and also have official information that holds up when the user checks it. If either is missing, the booking goes elsewhere.

Takeaway for Brand Marketers

1. Aim for the second tier. Generic "most popular" queries go to heavily documented landmarks. The winnable space is in themed and "hidden gem" sub-lists, such as poetry routes, autumn scenery and family-friendly options. Build content around the themes each model likes to generate.

2. Map your presence to each model's home ecosystem. Fliggy for Qwen, Meituan and Baidu for Wenxin, Douyin for Doubao, and WeChat for Yuanbao. Audit all four before the next holiday, not only Trip.com.

3. Get covered as part of the destination. Hotels, airlines and experiences show up when content presents them as part of a destination (as Shanghai Disney is), not as vendors mentioned after the destination is chosen.

4. Don't compete with the content factories on volume. Beat them on accuracy. Publish current prices, reservation rules and seasonal opening information on official channels in a structured, crawlable form. When the AI gets it wrong and the user checks, your official page is what they see.

5. Measure again after the holiday. Jinkoubei plans to check the models' "prediction hit rate" once the break is over. Brands should run the same comparison on themselves: which models named you before the holiday, and did bookings from those channels move?

Related: See how travel and hospitality brands score across Doubao, Kimi, DeepSeek, Qwen, Wenxin and Hunyuan on the hubGEO brand index, and read our earlier analysis of hotel and airline brands in China AI travel queries.