Original · Unique Research · 2026-04-14
Editor's note: The report and its judgments belong to the original Chinese author. This English rendition retains the full data analysis, ranking methodology, concept definitions, metric definitions and research disclaimer. All traffic, monthly active user, and annualized revenue figures are Unique Research estimates or source claims, not independently audited findings. The revenue estimation methodology and ±10% average absolute error rate are as stated in the source. Company and product names are retained in their original English or transliterated forms where official names are unverified. Ranking tables in the source reference external data at 100aiapps.cn; the "complete data available at 100aiapps.cn" placeholders are preserved as in the original.
Unique Research AI Top 100 Ranking
From "Free Usage" to "Paying for Capability"
The ranking change is only the surface. What is truly worth watching is how users are moving from "come take a look" to "willing to pay for capability."
Let us start with a fact obscured by traffic numbers: OpenClaw surpassed Manus in March visits, 28.78 million versus 28.77 million.
But if you look closely at this data, you will find a more important question than this ranking: why did Manus's active users grow 39% at the same time it was overtaken? Why did Claude's web端 nearly double in one month, while ChatGPT's growth rate was only 7%? Why did the open platforms of MiniMax, Kimi, and DeepSeek almost simultaneously explode in March?
The answers to these questions point to the same thing: the AI traffic landscape is not just being reordered—the way money flows is also undergoing a structural shift. The migration of users from "free usage" to "paid" is appearing for the first time in measurable form in March's data.
OpenClaw Surpassed Manus, but the Winner Is Not Itself
OpenClaw is an open-source project. Of its 28.78 million visits, a considerable portion comes from nodes that have grown around it: ClawHub (8.53 million visits, +161% month-over-month), EasyClaw (330,000, +387%), QClaw (2 million), and nanoclaw (260,000). If you add up the traffic of the entire claw ecosystem, the domestic and international combined total already far exceeds Manus as a single point.
This is the classic path by which an open-source project crushes a closed product: not through its own extreme refinement, but through the aggregate amplification of distributed nodes. Every claw-type product consumes OpenClaw's brand and technology foundation, while simultaneously feeding traffic and user awareness into the entire ecosystem. This structure of "parasitism and symbiosis coexisting" is an advantage no single product can replicate.
Manus's 8.98 million active users and 39% growth rate show it has not lost its footing—the entire agent赛道 is expanding, and Manus has simply shifted from "the only entry point" to "one of the top players." Traffic has been diverted, but the user base has not been lost. This point is important: when an ecosystem begins to form, first movers do not necessarily lose, but their relative positions get repriced.
There is also an extreme data point worth noting: openclawmp.cc ("the seafood market") had 100,000 visits this month, up approximately 16,000% month-over-month. Its volume is negligible, but it tells us the ecosystem's boundaries are still very blurry, new entry points continue to emerge, and the barrier to participation is extremely low. This ecosystem is far from the convergence stage.
Three Layers of Logic Behind Claude's Doubling
Claude's March web端 visits were 61.37 million, +111% month-over-month; active users were 66.99 million, up 80%. For a product that is already the world's third-largest AI chatbot, nearly doubling in one month.
First layer: The OpenClaw ecosystem is driving traffic to Claude. A large number of claw-type applications call the Claude API, ultimately converting API traffic into direct visits to claude.ai.
Second layer: Claude Code is creating an independent growth flywheel. After developers embed Claude Code into their workflows, daily debugging, code commits, and documentation writing all flow back to claude.ai itself, forming high-frequency usage habits. User stickiness at this layer is an order of magnitude higher than ordinary chatbots—after all, what OpenClaw can do, Claude Code can also do.
The third layer is the moat brought by revenue structure. Anthropic disclosed in early April that its annualized revenue exceeded US$30 billion, surpassing OpenAI (approximately US$24–25 billion). The more critical figure: approximately 80% of Anthropic's revenue comes from enterprise customers. Enterprise contracts do not quickly流失 because a new product is launched; whereas ChatGPT's consumer subscriptions are more easily replaced by cheaper, fresher products. Claude went from US$1 billion ARR in early 2025 to the current US$30 billion in 15 months. This is not just fast growth—it is higher-quality growth. Behind every dollar of new revenue is an enterprise customer embedded in a workflow, not just a consumer on a monthly subscription plan.
Domestic March: Open Platforms Collective Explosion
This is the most noteworthy structural signal in March's data.
MiniMax Open Platform: 4.69 million visits, +133% month-over-month, 1.27 million active users, +82%. Kimi Open Platform: 2.37 million visits, +130% month-over-month, 780,000 active users, +76%. DeepSeek Open Platform: 8.86 million visits, +66% month-over-month, 3.48 million active users, +33%. SiliconFlow: 2.37 million visits, +59% month-over-month. Infinigence (无问芯穹): 190,000 visits, +266% month-over-month, 80,000 active users, +237%.
Five platforms, almost all densely exploding in the same month—this is not a coincidence.
The agent development热潮 stirred up by OpenClaw in China is the most direct driver: a large number of developers are replicating or building claw-type applications and need stable, billable APIs. They are no longer satisfied with free tiers, nor do they rely on a single platform—instead, they allocate budgets based on model capability, call cost, and stability. This is a consumption behavior different from 2023: back then, payment was consumers subscribing to AI products; now, payment is developers and enterprises paying for capability. The former is C-end logic, the latter is B-end logic—different transaction amounts, different renewal logic, and completely different strategic value to platforms.
This turning point in China's AI market is more important than the traffic rise or fall of any single product. It means the commercialization of the AI industry in China is shifting from "running user volume" to "running API revenue," and the value of the infrastructure layer is beginning to be repriced by the market.
A Few Numbers That Should Not Be Overlooked
Microsoft Copilot: 33.66 million active users, +66% month-over-month. This is growth with almost no social media buzz—Copilot does not appear in spontaneous user discussions, but it is quietly penetrating enterprise desktops, completing silent accumulation through Windows built-in and Microsoft 365 integration. 33.66 million MAU, +66%—a top-tier number in any赛道, but because it has no product persona, it is often overlooked. This kind of "not discussed but users genuinely exist" growth is often the most stable.
Google Stitch: 12.91 million visits, +105%; 4.6 million active users, +136%. After Stitch's update, UI designers said the pressure was high. The outside world has long thought Cursor and Lovable are competing, with Google as a latecomer. But March's numbers show the situation is changing: 4.6 million active users, roughly the same量级 as ClawHub (2.98 million), and still accelerating. Google's staying power in this direction may be underestimated by the market.
NotebookLM: 43.99 million active users, already surpassing Grok (42.46 million), ranking fourth in the global MAU list. A knowledge management tool's active user count surpassing a top-tier conversational product indicates that the market for deep knowledge processing is much larger than the industry expected. Moreover, NotebookLM and Gemini's content sources are being打通, and Google is using these two pieces to build a closed loop of "conversation + deep knowledge"—once this closed loop forms, a pure AI chatbot will find it hard to compete.
candy.ai: 21.49 million active users, +35%. Emotional companion products have long been absent from AI discussions, but 21.49 million active users is a number no analyst should overlook. This category has higher user stickiness than tool类 products and stronger willingness to pay than conversational类 products. Maintaining 35% growth at such a large scale indicates that demand is far from saturated.
Conclusion
If March's data were summarized in one sentence, it would be this:
Traffic is being redistributed, but the real variable is who first completes the leap from "user count" to "payment capability."
OpenClaw surpassing Manus is a milestone, Claude's ARR surpassing ChatGPT is a milestone, and the collective explosion of domestic open platforms is also a milestone. What these three milestones共同 point to is: this round of AI competition is entering the second half. The rule of the first half was "who can pull more people in"; the rule of the second half is "who can make users genuinely pay for capability."
Only the product that completes this leap first is the true winner.
Unique Research — Authoritative Institution for Global AI Market Insights
The details of Unique Research's March 2026 AI Web Ranking are as follows:
AI Website Traffic Ranking: TOP 100 ranking of AI Web products by visits and monthly active users, separated into global and China markets.
All ranking lists simultaneously provide growth-rate rankings,方便 investment institutions discover potential projects and entrepreneurs and developers discover potential opportunities.
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01. AI Website Traffic Ranking
1.1 Global AI WEB TOP 100 by Monthly Visits
Based on its independent research of the AI industry and continuous tracking of thousands of global AI companies and nearly 10,000 AI products, Unique Research ranks the top 100 AI WEB products globally by cumulative visits in the current month. The specific ranking is as follows:
For complete data, please visit 100aiapps.cn; all visible data can be copied
For complete data, please visit 100aiapps.cn; all visible data can be copied
1.2 Global AI WEB TOP 100 by Monthly Active Users
Based on its independent research of the AI industry and continuous tracking of thousands of global AI companies and nearly 10,000 AI products, Unique Research ranks the top 100 AI WEB products globally by active user count in the current month. The specific ranking is as follows:
For complete data, please visit 100aiapps.cn; all visible data can be copied
For complete data, please visit 100aiapps.cn; all visible data can be copied
1.3 Domestic AI WEB TOP 100 by Monthly Visits
Based on its independent research of the AI industry and continuous tracking of thousands of global AI companies and nearly 10,000 AI products, Unique Research ranks the top 100 AI WEB products by Chinese entrepreneurs targeting the domestic market, sorted by cumulative visits in the current month. The specific ranking is as follows:
For complete data, please visit 100aiapps.cn; all visible data can be copied
For complete data, please visit 100aiapps.cn; all visible data can be copied
1.4 Domestic AI WEB TOP 100 by Monthly Active Users
Based on its independent research of the AI industry and continuous tracking of thousands of global AI companies and nearly 10,000 AI products, Unique Research ranks the top 100 AI WEB products by Chinese entrepreneurs targeting the domestic market, sorted by active user count in the current month. The specific ranking is as follows:
For complete data, please visit 100aiapps.cn; all visible data can be copied
For complete data, please visit 100aiapps.cn; all visible data can be copied
02. Research Statement
2.1 Data Notes
The AI product revenue data involved in this report, article, ranking, or charts is based on real-time tracking of redirect traffic from AI product official websites to payment gateways (such as Stripe), combined with time series analysis, to deeply analyze historical visits, monthly active user fluctuations, and pricing strategy changes, thereby constructing a dynamic revenue evaluation model. The model's core parameters are determined through a triple verification system of paid conversion funnel monitoring, reverse calibration of enterprise-disclosed data, and comparison with industry benchmark conversion rates, and are promptly compared and corrected with enterprise financial reports, financing announcements, and authoritative media disclosures. Through sampling verification, the average absolute error rate between predicted values and actual data is stable within ±10%, with accuracy reaching industry research-grade standards.
The AI product traffic data involved in this report, article, ranking, or charts is based on multi-source data integration and Unique Research intelligent algorithm processing, with the monitoring scope strictly limited to users' direct access behavior through official applications and websites. Specifically, this data only covers users' direct access to AI products through websites and native applications, and does not include traffic data generated by the following access methods: browser plugins/extensions, desktop client software, WeChat/Alipay mini-program ecosystems, embedded services on third-party platforms such as Discord, local deployment of open-source models, API interface calls, and other non-direct access scenarios. This data focuses on monitoring core end-side access behavior of AI products, aiming to objectively reflect the direct usage of mainstream user terminals.
Given the complexity and dynamism of data collection and processing, as well as the constantly changing market environment, the displayed data may contain a certain degree of error and omission. Therefore, this data should be regarded as a reference basis for research and analysis, aiming to provide users with a window for deeply understanding the AI product market, rather than a definitive basis for directly formulating specific investment strategies or providing consulting advice.
Data coverage expansion notes:
We are actively developing and testing monitoring models for the following emerging fields, expected to be gradually included in future quarterly reports:
AI Agent ecosystem
AI hardware device sales and activity
Large model API call scale estimation
Stay tuned.
2.2 Concept Definitions
• Geographic dimension
Overseas AI products: Products founded by non-Chinese entrepreneurs or teams, primarily targeting the global market (including but not limited to their domestic market).
Domestic AI products: Products founded by Chinese entrepreneurs or teams, primarily targeting China's local market.
Going-global AI products: Products founded by Chinese entrepreneurs or teams, but with the main market target positioned overseas (non-Chinese local market).
• Functional dimension
AI-native applications: Applications that deeply integrate artificial intelligence technology and algorithms from the initial product design, whose core value, business processes, or user experience completely rely on AI technology. These applications not only use AI to optimize or enhance existing functions, but take AI as their core component—without AI technology, these applications would cease to exist or lose their core value.
AI-feature applications: Applications that enhance existing functions or provide entirely new functions by integrating or embedding AI technology on the basis of original business logic and application frameworks. These applications may already have mature business models and market positioning, but through the introduction of AI technology, can significantly improve efficiency, enhance user experience, or create new value points.
AI-ecosystem applications: Platform-type applications that provide support, connection, or communication facilitation for the AI ecosystem composed of AI technology developers, application developers, service providers, and end users. These applications are not limited to the technical level, but also involve multiple dimensions such as market, community, and resource sharing, aiming to promote the popularization, innovation, and cooperation of AI technology.
2.3 Metric Definitions
• WEB data metrics
Visits: The total number of all visits to a website within a specific time period (such as one month), used to measure the scale of website traffic. Page views within a continuous active period are counted as the same session, while a user who reactivates after an interval of more than 30 minutes or starts a new day is regarded as a new visit, thereby comprehensively and accurately measuring website traffic and visitor activity.
Unique Visitors: The number of independent IPs that visit the target website within a specific time period (such as one month). If someone visits a website on multiple days within a month, they are only counted as one unique visitor.
Subscription Revenue (ARR): The total revenue obtained by a website through subscription services provided to users within a certain period (such as one year), and this revenue excludes advertising revenue, transaction commissions, and professional services with one-time characteristics.
• APP data metrics
Downloads: The number of times an App is downloaded by users within a specific time period (such as one month). Usually measured by the number of downloads of a single App on app stores (such as App Store, Google Play, etc.). Downloads are one of the important indicators for measuring an App's popularity and user attractiveness, and can also reflect the effectiveness of App promotion and marketing activities.
Active Users: The number of independent users who have performed at least one activity within a specific time period (such as one month). Active users is an indicator for measuring user participation and activity level within a specific time period, usually used to evaluate an App's user scale and user activity.
In-App Purchase Revenue (IAP): Revenue generated by users' purchase behavior in an App to obtain virtual goods, additional services, advanced features, etc. This excludes advertising revenue, direct user payments (such as tips), and revenue from third-party Android app stores.
2.4 Free Disclaimer
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