Original · Unique Research · 2026-05-11
Editor's note: The first-person report and its judgments belong to the original Chinese author. This English rendition retains the opening essay, all data sections (OpenClaw, Claude, Grok, 5M+ MAU growth list, video generation, domestic market, funding analysis, AI tools), the directional conclusions, the Unique Research authority introduction, the ranking methodology section, and the complete research statement including all definitions and disclaimers. All traffic, revenue, valuation, funding and market-share figures are Unique Research estimates or source/speaker claims, not independently audited findings. Product names, company names, personal names and technical terms are preserved as source-stated. The direct quotations from Dario Amodei, Boris Cherny, Andrej Karpathy, Huang Renxu and Demis Hassabis are preserved as translated in the source. Company and personal names are transliterated where official English forms remain unverified. Eighteen source images are declared but not processed in this backfill.
Unique Research Global AI Web Ranking Observation
OpenClaw Halved, Claude Surged 34%, xAI Dissolved—The Real Watershed for the AI Industry Has Arrived
Based on Unique Research's April 2026 Global AI Web Application Data
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First, a coordinate for feeling: at the end of January this year, OpenClaw launched on GitHub and within 48 hours climbed to the top of the world's most-watched open-source projects, with stars surpassing 136,000. That was the hottest month for the Agent concept, when everyone was asking "is the Agent era really here?"
The April data is out. The tide that should recede has receded, and what should keep rising is still rising.
OpenClaw Halved
At its peak, OpenClaw had close to 12 million unique visitors and nearly 29 million monthly visits.
April data: monthly visits fell to 14.2 million, down 50.67% month-over-month; unique visitors 6.31 million, down 46.98% month-over-month. ClawHub visits -55%, and the Agent community Moltbook's unique visitors fell 71%. The entire Claw-type ecosystem has almost collectively cooled.
But this decline has a very specific trigger—on April 4, Anthropic announced that its subscription service would no longer cover third-party tools such as OpenClaw, effective the same day, giving users only one day to migrate. From that day, Claude Pro users using OpenClaw had to purchase additional usage packs or configure their own API Key. Boris Cherny, head of Claude Code, explained that "third-party tools put excessive pressure on the system." This policy implementation directly cut off OpenClaw's largest source of free usage.
This has nothing to do with OpenClaw's own technical value. Its founder, Peter Steinberger, has joined OpenAI to continue advancing the Agent direction. He himself has reflected: this project received as many as 16 security vulnerability reports per day and was once the target of an attempted attack by North Korean state-level hackers. His judgment is that granting Agents more permissions and security risks always coexist, and the next round needs a more solid engineering foundation.
So OpenClaw's ebb is the dual result of policy cutting off free traffic sources,superimposed the industry sentiment shifting from excitement to冷静.
Claude, the Only One Sprinting Among the Top
ChatGPT remains the absolute ruler, with 5.5 billion monthly visits and nearly 500 million MAU, but this month saw a slight -3.84% decline. Gemini grew steadily, with monthly visits +6.38%. DeepSeek was also steady, with monthly visits +4.81%.
Claude's data was as eye-catching as last month: monthly visits 823.5 million, +34.18% month-over-month; MAU 89.69 million, +33.89% month-over-month. Among all top products, its growth rate was nearly five times that of second-place Gemini.
This number highly aligns with what happened in April. In mid-April, Claude Opus 4.7 was released, scoring 87.6% on the SWE-bench programming benchmark, 6.8 percentage points higher than the previous generation. The simultaneously launched Claude Design caused Figma's stock to drop 7.28% that same day—just the release of a design tool triggered such a strong industry reaction. In the same month, Claude Managed Agents entered public beta, with Notion, Rakuten and Asana as first adopters, accelerating enterprise customer implementation. At month's end, Anthropic's valuation surged to US$1 trillion in the secondary market, immediately followed by Google announcing up to an additional US$40 billion investment and a commitment to provide approximately 5GW of computing power over five years; Amazon announced up to another US$20 billion the same week.
At the Code with Claude developer conference, Dario Amodei said: "We prepared computing power for 10x growth, and the actual annualized growth rate in Q1 was 80x. It's crazy—we can't keep up." Anthropic's annualized revenue trajectory is as follows: US$87 million in January 2024, surpassing US$1 billion in December 2024, approximately US$9 billion at the end of 2025, US$14 billion in February 2026, US$19 billion in March 2026, and reaching US$30 billion by April 2026. Salesforce took 20 years to travel this path; Anthropic took less than three.
Amodei also said: "Software engineers are the earliest group to adopt new technologies. The way they use AI now is a preview of how the entire economy will be transformed."
Grok's Decline and a Bigger Story
Among mainstream large models, the most obvious decline in April was Grok: monthly visits -14.43%, MAU -7.13%. This is the worst product-side performance against the backdrop of the loudest voice and the most funding.
On May 6, Musk announced that xAI was dissolved and merged into SpaceX, renamed SpaceXAI. All 12 co-founders left within less than three years; by the end of March the last co-founder had departed, and it was only a few months from then to the formal dissolution. On the same day, SpaceXAI leased the entire Colossus 1 data center—220,000 Nvidia GPUs, over 300 megawatts of computing power—to Anthropic.
The logic behind Grok reaching this point is not complex: the collective departure of the core team reflects directional disagreements; Grok'scontinuous落后 in programming capability made it lose out in the most critical competitive dimension; and the burn rate of approximately US$1 billion per month is unsustainable. Musk himself even publicly admitted that even xAI's own employees use Claude to write code.
Musk's next step looks clearer: no longer competing head-on with OpenAI and Anthropic on models, but pivoting to become the "utility provider" of the AI era, using SpaceX's rockets, Starlink's network and Colossus's computing power to do infrastructure-layer business. Leasing computing power to Anthropic—this step looks like bowing down, but is actually repositioning in a different track.
We will continue to track Grok's trajectory within the SpaceXAI system.
Products with 5M+ MAU Still Growing at Double Digits
This perspective is more interesting than the growth ranking. Many products in the growth ranking are small-base effects, but a product that already has over 5 million MAU and is still growing at more than 10% per month indicates that it has crossed the "novelty-driven" stage—demand is real and the market has not yet reached its ceiling.
In April, the products meeting this condition were: Claude (89.69M MAU, +33.89%), NotebookLM (48.65M MAU, +10.61%), Microsoft Copilot (38.06M MAU, +13.06%), Suno (16.97M MAU, +10.49%), Meta AI (10.11M MAU, +24.29%), Hugging Face (10.23M MAU, +17.58%), Adobe Firefly (8.95M MAU, +30.1%), SeaArt AI (6.31M MAU, +13.96%), Ollama (5.92M MAU, +36.84%), Genspark (5.63M MAU, +16.74%).
Several of these are particularly worth mentioning. Ollama is a tool for running large models locally, aimed at developers and researchers. With 5.92M MAU still growing at +36.84%, this indicates that the demand for "wanting to control the model yourself without relying on the cloud" is rapidly expanding—aligned with enterprise demand for data privacy. Meta AI, leveraging the WhatsApp and Instagram entry points, has over 10 million MAU and is still growing at +24.29%; this path will continue to accelerate. Adobe Firefly's +30.1% is backed by embedding AI capabilities into existing workflows such as Photoshop, where existing users naturally migrate to AI workflows—this is the most stable growth logic and the hardest to replace.
These ten products share one common trait: they are all doing something that was difficult or expensive before AI existed, rather than making AI versions of existing tools.
Video Generation, This Time Is Different
At the top of the April growth ranking, video generation products appeared densely. Pexo monthly visits +1871% month-over-month—a going-overseas product targeting the overseas short-video creation market; Flova (+114%) and aicut (+117%) are also in the going-overseas direction. On the domestic side, OiiOii MAU 120K +74%, and ByteDance's Jichuang monthly visits 360K +43%.
This is not just a product-level matter. In April, Volcano Engine's Seedance 2.0 fully opened API access to enterprise workflows; afterintegrate by the short-drama and comic-drama industries, efficiency improvements reportedly reached 80% to 90%. Alibaba's Wan2.7 series updated video and image capabilities in the same month, supporting ultra-long text rendering in 12 languages. The foundational capabilities of creation tools are rapidly improving, and going-overseas video generation tools have正好 caught this wave of capability dividends.
Video creation demand is a rigid need globally. When the generation threshold drops from "requires editing skills" to "input text and get a video," the increase in penetration is structural. Going-overseas creation tools have found their incremental space in this window.
Domestic Market: Stock Game, But B-End Is the Main Battlefield
Domestic top applications were overall flat in April. DeepSeek monthly visits +4.81%, domestic #1, steady but not explosive. Doubao +1.35%, nearly flat. Quark -10.78%, Kimi -10.74%, Tencent Yuanbao -15.39%, Baidu AI Search -9.88%—most of these declining products are pullbacks after the traffic peak around Spring Festival.
The really interesting signal is on the B-end. DeepSeek Open Platform MAU 4.39 million, +26.18% month-over-month, monthly visits +30.99%. This is the opposite of the C-end's -10% level. In late April, DeepSeek V4 preview was officially launched and open-sourced, with 1.6 trillion parameters and 1M context support; V4-Pro had a limited-time discount during theintegrate period. This release node most likely directly drove developer call volume on the open platform. The meaning is clear: DeepSeek's individual user traffic is stabilizing, but developer and enterprise users are still growing rapidly. This is a more solid signal than C-end visits—money follows the B-end.
Several small products in the domestic growth ranking are worth noting: Meitu's RoboNeo MAU 410K +51.25% (focused on e-commerce image generation), Kira MAU 180K +56.3%, OiiOii MAU 120K +74% (video generation). The common trait of these products is vertical scenarios, quick visible results, and strong virality. This combination will continue to be effective in creative tools.
DeepSeek and Kimi's Funding Moment
From April to now, changes in China's AI primary market have been livelier than the product side.
First, in mid-April, DeepSeek—silent for three years and never raising funding—began contacting investors. Three weeks after the news broke, its valuation was reportedly raised four times: approximately US$10 billion in early April, over US$20 billion by April 22 when Tencent and Alibaba were reportedly in talks, and possibly US$45 billion on May 6 when the national big fund介入 talks. Liang Wenfeng himself also increased his personal direct stake from 1% to 34% on April 27, reportedly to participate in this round in his personal name.
On May 6, Kimi (Moonshot AI) was reported to be about to complete a new US$2 billion funding round, with a post-money valuation exceeding US$20 billion, led by Meituan Dragonball. In less than half a year, Kimi's cumulative funding has exceeded US$3.9 billion, while its C-end monthly visits in the same period were -10.74%—user numbers are weakening, but capital is doubling down.
These two events together tell the same judgment: the competitive logic of large models has changed. From technology competition, it has entered a stage where computing power, talent and capital are competing simultaneously. DeepSeek's story of "training a world-class model with US$5 million"—in the face of V4's trillion-parameter level, training costs have already膨胀 to the US$1 billionscale. Without raising funding, talent cannot be retained and computing power cannot be run. Good technology never lacks buyers—this is the essence of this funding boom.
Cross-referencing globally: the Big Four tech giants' Q1 earnings were released the same week. Google, Meta, Microsoft and Amazon's combined annual capital expenditure is close to US$700 billion, all pouring money into AI infrastructure. With this number on the table, the computing-power arms-race pressure on domestic AI companies is clear at a glance.
Claude Code, Codex, Cowork and Mac Apps—What Do These Have to Do with You?
The密集 updates of AI tools in recent months have caused审美 fatigue, but several directions are worth mentioning separately, because they are changing the threshold of one thing: who can use AI to make something truly useful.
Events that happened densely in April: Claude Opus 4.7 released, simultaneously updating Claude Code's scheduled tasks and API trigger functions (Pro 5 times/day, Max 15 times/day); Anthropic launched Claude Design, which can generate prototypes, PPTs and brand systems through conversation; OpenAI's Codex Mac version added computer control and an in-app browser; Google's Gemini native Mac app launched on April 15, supporting Option+Space invocation and screen content awareness. The last of the desktop AI three has landed.
Cat Wu, head of Anthropic Claude Code, shared an internal detail: in the AI era, the product lifecycle has shortened from 6 months to 1 week or even 1 day. When the cost of writing code approaches zero, deciding "what to make" and "what counts as a good experience" becomes the most valuable capability.
Andrej Karpathy put it more directly: we are entering the Software 3.0 era, where handwritten code is no longer needed—instead, AI is driven by prompts. He believes that the core value of humans in the future will become "taste, aesthetics and architectural judgment"—deciding what to do, and AI fills in the details.
Huang Renxu sent an internal email at the end of April, requiring all 10,000 Nvidia employees—including HR, finance and legal—to fully adopt AI programming tools, on the grounds that "the era when everyone is a developer has arrived." His own statement at GTC was: the AI industry is entering a new stage with computing power as the core resource and systems engineering as the dominant force; Token is the new commodity, and the inference inflection point has arrived.
DeepMind CEO Hassabis said in a YC conversation at the end of April that current AI still has three unsolved fundamental problems in continuous learning, long-range reasoning and memory mechanisms, and that 50% of the probability of achieving AGI still requires one or two key breakthroughs yet to be discovered. But he also believes that in scenarios with clear tasks and immediately verifiable results—programming, video generation, data processing—AI can already substantially take over.
What do these tools mean for ordinary people? The threshold is dropping. A person without an engineering background or design resources is gaining the ability to do things that previously only a team could do. How fast it is dropping can be measured by one detail: in April, Xiaomi's MiMo spent 4.3 hours writing from scratch a compiler assignment that Peking University undergraduates typically need several weeks to complete, and got a full score. This is not saying that AI will replace anyone, but rather: things that previously requireda large number of time and professional background are becoming things you can do "if you have an idea."
Several Directional Conclusions
Looking back at this April data, several logics of the industry are becoming clear.
Sentiment is ebbing, but demand is not. OpenClaw's cooling has specific reasons, but the deeper layer is: for prompt-driven, out-of-the-box Agents, users have perceived the gap between what they can do and what they cannot do. Hassabis said Agents are "close to handling complex tasks"; the data confirms that for simple and clear tasks, AI already handles them well, while complex tasks are still on the way.
The divergence in growth is more important than the total. In the top格局, Claude is growing rapidly, Grok is falling, Sora MAU -27.71%, Jimeng MAU -16.52%. All backed by giants, but the results are completely different. This round of competition has entered the "user real choice" stage—money and voice do not equal product votes.
Domestic incremental is shifting to the B-end and infrastructure. DeepSeek Open Platform +26%, while the Chatdevice is原地踏步; Kimi is raising funding while its C-end weakens. The center of gravity of commercialization is migrating from traffic to APIs and enterprise integration.
Computing power is the foundation of this competition. Huang Renxu said AI is a "five-layer cake," with energy at the bottom. Musk leased 220,000 GPUs to Anthropic, saying "in two to three years, space will be the place with the lowest AI computing power cost"; the Big Four's annual capex is close to US$700 billion; Anthropic and Google signed a 3.5GW long-term computing power agreement—this level of infrastructure game has already exceeded the dimension of products and models, entering the scale of great-power competition.
Unique Research — Authoritative Institution for Global AI Market Insights
The details of Unique Research's April 2026 AI Web Ranking are as follows:
AI Website Traffic Ranking: TOP 100 ranking of AI Web products by visits and monthly active users, distinguishing between global and China markets.
All ranking lists simultaneously provide growth rankings,convenient investment institutions to discover potential projects and entrepreneurs and developers to find potential opportunities.
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This AI product ranking is permanently open source and free, with complete methodology and raw data supporting full reproduction.
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01. AI Website Traffic Ranking
1.1 Global AI WEB TOP 100 by Monthly Visits
Based on its own independent research of the AI industry and continuous tracking of thousands of AI companies and nearly 10,000 AI products globally, Unique Research ranks the top 100 AI Web products globally by cumulative visits for that month, 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 own independent research of the AI industry and continuous tracking of thousands of AI companies and nearly 10,000 AI products globally, Unique Research ranks the top 100 AI Web products globally by active user count for that month, 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 own independent research of the AI industry and continuous tracking of thousands of AI companies and nearly 10,000 AI products globally, Unique Research ranks the top 100 AI Web products by Chinese founders targeting the domestic market, by cumulative visits for that month, 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 own independent research of the AI industry and continuous tracking of thousands of AI companies and nearly 10,000 AI products globally, Unique Research ranks the top 100 AI Web products by Chinese founders targeting the domestic market, by active user count for that month, 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 Description
The AI product revenue data involved in this report, article, ranking or chart is based on real-time tracking of the跳转 traffic from AI product official websites to payment gateways (such as Stripe), combined with time series analysis, deeply analyzing historical visits, monthly active user fluctuations and price 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 of industry benchmark conversion rates, and are promptly compared and corrected with corporate 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 standards.
The AI product traffic data involved in this report, article, ranking or chart is based on multi-source data integration and Unique Research's 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 the core end-side access behavior of AI products, aiming to objectively reflect the direct usage of mainstream user terminals.
Given the complexity and dynamics 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 Note:
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 home market).
Domestic AI products: products founded by Chinese entrepreneurs or teams, primarily targeting China's domestic market.
Going-overseas AI products: products founded by Chinese entrepreneurs or teams, but with the primary market target positioned overseas (non-China domestic market).
• Functional Dimension
AI-native applications: applications that, from the initial product design, deeply integrate artificial intelligence technology and algorithms, whose core value, business processes or user experience are entirely built 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 not exist or lose their core value.
AI-function applications: applications that, on the basis of original business logic and application frameworks, enhance existing functions or provide entirely new functions by integrating or embedding AI technology. These applications may originally 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 promote communication for the AI ecosystem composed of AI technology researchers, 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 Indicator Description
• WEB Data Indicators
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 a new day begins 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 providing subscription services to users within a certain period (such as one year), and this revenue does not include advertising revenue, transaction commissions and professional services and other one-time revenue components.
• APP Data Indicators
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 an app store (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 been active once within a specific time period (such as one month). Active users is an indicator for measuring user participation and activity 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. Here, advertising revenue, users' direct payments (such as tips, etc.) and third-party Android app store revenue are excluded.
2.4 Free-Use Statement
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