The Top 100 GenAI Products, Ranked and Explained

0:01Consumer activity typically lags by 6 to 9 to 12 months. What's happening on the research side? So many of these assumptions and that's why the assumptions they seem intuitively correct are going to turn out to be incorrect. We are finally on the verge of AI video starting to really work. It sort of follows the trend of AI decreasing the cost of creation in every way. 95 % of YC companies are now building using those tools. I think compared to where we're going to be, we're still incredibly early. This month, our consumer team at A60Z dropped our fourth installment of the Gen AI 100 list, a list of the top 50 AI first web products and mobile apps based on unique monthly visits and active users.

0:47And as our consumer teams set themselves, in just six months, the consumer AI landscape has been redrawn. Some products surged, others stalled, and a few unexpected players rewrote the leaderboard overnight. In today's episode, we explored the latest rankings and the pivotal AI moments of the last few years. Mid -journey and character AI both came out before Chatt -Tubi -T. Remember Snapchats, my AI, the Balenciaga Pope? Coke did their Christmas ad. Each one of those unlocks broke down the assumptions that many of us held prior, and have helped culminate hundreds if not thousands of AI applications that are now vying for our attention.

1:30The app store is going to be chaos. Yeah, I know. So which applications top the charts this time around? Whether household brand names or tools that you may have never heard of. Plus, where does this flurry of activity, place us on the adoption curve. And what trends did I, like AI video or vibe coding, that give us a window into what's to come. Finally, this fourth edition of the list is actually the first time that we broke out with actually making money. And today we have A16C consumer partner Olivia Moore and General Partner Anisha Charya to break down all of the above. Of course, if you'd like to see the full list of the top 100 GNI apps, head on over to A16C .com slash Genai100 -4, or you can check the link in our show notes.

2:19Okay, let's get started. As a reminder, the content here is for informational purposes only. Should not be taken as legal, business, tax, or investment advice, or be used to evaluate any investment or security, and is not directed at any investors or potential investors in any A16Z fund. Please note that A16Z and its affiliates may also maintain investments in the company's disgust in this podcast. For more details, including a link to our investments, please see a16c .com slash Disclatures.

2:53We're back for the fourth edition of the Gen AI 100 list. You guys have been working hard and tracking the consumer landscape for years now, but specifically for the last two and a half years since we really had that chat GPD moment. Tell me more about how you're tracking that ecosystem and how that comes through in this list. Yeah, it's super fun. This is one of my favorite reports that we've put together a couple times a year. We track the consumer AI landscape through what we do every day, which is like meeting with consumer AI startups that come to pitch us, seeing what goes viral on Twitter.

3:23But actually, there's a whole separate set of companies and products that might be reaching the true mainstream consumer that might not even be marketing themselves as AI products, but they're powered by and made possible by AI. And so the whole original purpose of this report was to see how much overlap is there between those two categories and what is the actual everyday person who might not know that they care about AI using in their day -to -day. That's great. And so talk about the methodology, like what makes it onto this list or not, because to your point, there's certain household names that you might see on Twitter or have that viral moment.

3:57But I think some people might be surprised to see what made it onto this list. So it's entirely based on data. We have two lists here, the top 50 on web and the top 50 on mobile. So the top 50 on web, we use a data provider called similar web, which tracks every single website globally. And we essentially go down in descending order of how many visits they get each month. For this report, it was January 2025. And then we go and we pick the first 50 of those that have the most monthly visits that are Genai first products. We do something similar on mobile, but a different data set from sensor tower.

4:34For mobile, we look at monthly active users on the app, and then again, we pick the top 50 that are Gen AI products. And then for the first time ever, we actually looked at the top 50 on mobile by revenue, which we hadn't done before, and it was a really interesting experiment, because the lists were pretty non -overlamping. Totally, and we'll get to that. Yes. We've been in this AI ecosystem for a few years now. in your eyes, what were the pivotal moments that led up to this point in time where we have, like you said, 50 and mobile, 50 on desktop and a whole lot more in the wider ecosystem? You often say actually it's usually like the papers are written and then the models are developed and then applications are built on top of it.

5:14So the consumer activity typically lags by six to nine to 12 months what's happening on the research side. So maybe just from the consumer awareness or behavioral perspective, there's a couple moments for me. Actually mid -journey and character AI both came out before ChattGBT, which I think a lot of people don't know, but there was maybe these early niche communities of early adopters that were using both of those products in the summer and the fall of 2022 leading up to ChattGBT. And then post -ChattGBT things that just brought AI to consumer consciousness. So even remember Snapchats, my AI, with that little bot that appeared at the very top of your feet.

5:56And 150 million people used it. And for a lot of kind of younger consumers, that was actually probably their first real chance having a conversation with an LLM. On the image side, I think of the Valenciaga Pope, which was also, I think, spring 2020. Such a cultural moment. It was. And I think it made a lot of people realize for the first time that they should even be interested in AI images because they could be that good and that convincing. The first big AI music moment for me was, well, the BBL Drizzy song, which I think was... That was huge. Spring of 2024. And that also went mega viral. No book LM was another one.

6:34I think one of the moments where creative AI really shifted into almost enterprise consciousness was the end of last year when Coke did their Christmas ad. And a lot of that was generated by AI. And then, of course, the deep seek launch earlier this year. DeepSeek was so interesting because I think it sort of had become settled wisdom that it would be very hard for a horizontal model to get to mass consumer scale quickly again. Like chat GPT had done it and chat GPT had become a verb and that opportunity had already been explored. And now we see DeepSeek growing as quickly as it did. And there's actually a couple of interesting nuances to DeepSeek.

7:09So one, I think, important nuance is the fact that they released their reasoning model for free at scale. So previously you had to use O1 Pro and you had to pay chat, GPT's premium subscription to get access to it. The other thing was just the product execution around chain of thought, which we've talked about a lot and I think is pretty well understood. But the fact that it showed you its thought process in real time was just super captivating and now something that's become a step that every model takes. So I think it just really illustrates how early we are. We as sophisticated users and investors are looking for further and further refinements.

7:45And once in a while something like DeepSeek comes out of the clear blue sky and just blows away all assumptions. Totally. And that word specifically assumptions, I think is so key when you talk about these pivotal moments, I feel like you could actually match each pivotal moment with an assumption, like an assumption being, oh well, I could never trick me into thinking a picture is real when it's not. right? Or I would never actually listen to a top 100 song that's generated by AI or Chad Chippity is corner of the market. No one else can penetrate it, right? All of these assumptions that people are like, okay, sure.

8:15I was wrong about that prior one, but this one I'm pretty sure about. We're seeing just like months being the delta between assumptions being broken. And so to your point on the arc of the market or the industry, I could see an argument where people are like, oh, we're actually pretty far along because we've already slashed all of those assumptions. But on the other hand, I'm hearing we still have a long way to go. So maybe put us along that arc if we were to compare to the mobile era or the cloud era or previous technology era and are we in that early innovator stage still or are we somewhere else?

8:47I think we're still very much in the early adopter phase. In many of these categories, we're just arguably still in the infrastructure building era and moving into the application building era. It depends on the modality. Like now LLMs are Maybe people thought that was a problem, but then again, deep sea came in and upended all of that. There's a lot of things that are definitely not fully solved. Like AI video right now can generate great three or five or six second clips, but hopefully years from now, we have AI video that can generate minutes long or even hours long movies. And so I think compared to where we're going to be, we're still incredibly early.

9:23Here are two assumptions that I think are interesting because it may turn out the reality is the exact opposite. One is that AI will be very good at transactional interactions, but humans will still be the ones to build relationships and connection. So an example of that would be what kind of phone calls are AI going to be best at. And I think the assumption was, well, they'll be great at sort of scheduling and logistics and the exchanging of information and facts. But we've heard over and over that in many cases the AI's are more human than humans. They just have more patience, more nuance. They're never having a bad day, they're never hungover.

9:58So that's an interesting area of exploration. The other one that I think is interesting is the idea that humans will delegate work to the AIs, and the AIs will do it. Like, what if the AIs are the ones delegating the work to us? Perhaps AIs are really good at organizing work, and we're really good, and also get a lot of joy out of doing it. So I think so many of these assumptions, and that's why they're assumptions, they seem intuitively correct, are gonna turn out to be incorrect. Totally. And if we think about the report, maybe one important data point is the fact that we see so many newcomers still, right?

10:29If we were in that later part of the innovation curve, you might expect more stagnancy, you might expect to see the same players. But every time you guys build out this report, we're seeing all of these newcomers in this particular time, the fourth report we saw, 17 new companies on the web rankings in particular. You actually have this quote where you say, a few unexpected players rewrote the leaderboard overnight. So can you just speak to that in the movement that we're seeing? One of the biggest trends among the newcomers is we are finally on the verge of AI video starting to really work. Not just for people who are enamored by AI and willing to generate 100 times to get a good clip.

11:07But for people, yeah, but for people who actually want to make something creatively in a condensed time period. So we had three new video models on the list this time. and Kling, which are both Chinese models, and then Sora, which was OpenAI's model that was announced, I guess more than a year ago at this point, and finally was released. I think we'll see even more of a shake up here because VO2 is the new Google model that is even next level beyond that from what we've seen in testing, and that is probably finally gonna hopefully come out in the next three or six months. The other big category of newcomers, whether these vibe coding products, cursor made the list, it's more of an agentic ID for a technical audience, and then Bolt made the list, which is for a non -technical audience, where you basically go from a text prompt to a fully functioning web app.

11:59Even though they made the list, I think we've still seen there's a really significant portion of their users that are people who are in tech and are actually technical, but they might be using something like a Bolt or a Loveable, which made our brink list, which we can talk about, to maybe prototype something easier, and then export the code and go and play with it themselves. So I think we haven't quite seen the vibe coding products hit the true mainstream user in terms of someone who's never worked in tech or developed an app. I love this category. It's so fun and it's so satisfying to actually see your ideas come to life.

12:35In the case of Bolton Lovable, sometimes they are just sort of compelling interactive prototypes, more than they are full -fledged products, but that's usually enough to get a feel for whether this is something you want to invest deeper in. It sort of follows the trend of AI decreasing the cost of creation in every way, and people just trying more ideas. I know, just think about what that says about the untapped market of people who want to build things with code that this is on the top 50 list. And I think, honestly, both of them haven't had many apps built on them yet that have gone super viral.

13:09And when that happens, and I'm sure it will, those will become stories of their own, which will then increase awareness of the products of the true mainstream audience. I think we're gonna see a really interesting diversity or range of products built on these, which it might just be like, this is my app that I just use for my very specific niche pain point, or there might be people who never learned how to code who want to build a venture scale product on something like a bolt or a lovable, and so seeing how that plays out will be very cool. Yeah, I think there's two phrases I've heard that I like.

13:40One is sort of DIY or personal software, but never made economic sense to design software for one. Really, the other is disposable software, just as Suno and UDO made it possible to make a song just to capture a joke that would be irrelevant the next day. These products make it possible to create a product or an experience that may have an extremely short shelf life, like 20 minutes or a week or any other 20 -period. Let's talk about the brink list because that's completely new to this year's fourth generation. So what is the brink list and why add it? So the brink list is essentially the five companies that almost made the list and were right below the cutoff again purely based on the data.

14:20So we pulled the five websites and the five mobile apps. And I think honestly we were just curious to see what it would capture. We didn't quite know. The takeaway for me, it does reflect how fast things are changing because there were a couple of companies on the list, like Runway, Otter, UMACS, Across Web and Mobile, that have been on the core top 50 ranks in the past, but maybe they got just edged out by deep seek watching this time, and so they lost their spot for this ranking, but might be on there the next one, and they still have massive usage. And then the other trend that it caught was a rise in more recent products, like Cria made the list and Lovable made the list, that are very much on the kind of consistent upswing.

15:00And if it continues, we might see them on the main ranks and they haven't made the main ranks before. What did you predict that you would see on the list that you didn't really see there? Were there any surprises on that end? So one thing I thought we'd see more of is style transfer as an approach to scalable video. Because style transfer is just a much more tractable problem and has a lot lower cost of inference versus raw text to video. But researchers and product developers seem to be really going for it on text to video and we've seen more of that than I would have expected. The other things that we didn't see on this list that we have seen at the model level so that means maybe they'll be on the next list or like consumer voice products.

15:39There are a few of them but not a ton of them. Some of the new like the Gemini Flash model that can see what's going on on your screen and interact with you. Like I built something to yell at me if I go on Netflix or something. Like is reading my screen real detector. Yeah, and so it's like, it's free. We have you like, no, get back to work. Or like the new OpenAI operator model, which can actually interact with things on the browser level on your computer and get tasks done for you. Like pay a bill or make a graphic design or hire someone to landscape your yard, something like that. I think there's always a lag because the models have to be released to developers and they have to be tuned by the developers.

16:20And so it takes a while. but I would expect to see maybe an explosion of fun and unique and interesting products built on models like that on hopefully the next list or two because it feels like we really have seen an explosion on the model side and it is right there in terms of manifesting at the app level too. So one of the examples of this is deep research, which if you played with it is completely magical. But it's a primitive, right? It's not a product. It's something to build other things with. So it's really unclear if deep research is going to be used to write college thesis or is it going to be used to find the perfect meme to match a joke you want to make?

16:58And that's all going to be up to the app developers. And just to double click on that, because you could see maybe a world where deep research is just this like more broad horizontal application or you could see what you just described where developers are tailoring that to specific end use cases. Are you basically saying that you think the latter is more likely in terms of the progression of these models and apps? Not more likely, but I think it's under explored. If you come to deep research today, you have the blank page problem. And I'd love to see developers create some constraints that lead to unexpected outcomes.

17:29Yeah. Like the known or the prescribed use of deep research right now is basically market research reports. And it's amazing for that. I've used it for that a lot of times. But if you try other things like one day we were trying to trace the origin of a mean and deep research is like a hundred X better version of that. know your meme website that kind of goes through the history. Yes. And the etymology or however you describe it, how it helps me become a meme. I mean, that should be an app. Yeah, so there's lots of other use cases that aren't market research reports that could really benefit from an incredibly obsessive compelling model that will go and read every website.

18:06I'll be internet until it finds the answer. I love that. I've actually always wanted that for creators, because you know how there's the whole success over night. Phenomenal that everyone else things happens, but it's not true for most creators who are like, you take Mr. Beasties, like I literally counted to what? 100 ,000? Yeah. And then I did thousands of more videos until I, like something started to work. And I wish you could actually just see as you're saying history of a meme, but history of a creator. Like, when did the unlock happen? So those are the things that you thought might be on the list, but you didn't actually see there.

18:35What about the opposite? I think the fact that the vibe coding products, like the bolt and the cursors and loveables made the mainstream consumer list is just a testament to how widely they're used by the technical audience. Like they have gotten to saturation so quickly. I think Gary Tan had some tweet that like 95 % of YC companies are now building using those tools. So it's something that nearly every developer now is probably using, which was maybe a surprise to me how quickly we reach saturation. We've talked about this but a continuing surprise. So I don't know if it counts as one, but I still am surprised every time is how many companion products are on the list and also how many of them rank so high.

19:15I think we had three companion products in the top 10. Two of them were NSFW oriented. Maybe not surprising when you think about like traffic on the internet in general outside of AI, but a lot of people are even using them as like interactive fanfiction and some of the biggest fanfiction sites in the world are also top 100 top 200 global sites. So it makes sense in that way. And then I guess my last surprise would be there's actually quite a bit of consistency in the list over the past four versions. There's always new entrance, which is really exciting, but across the four lists there's now 16 companies on the web ranks who have made it every single time and have kept the street going, which is pretty remarkable when you think of how early we are in AI, but I think a testament to how those companies have cemented their brands, their products, their kind of, I guess, status and consumer consciousness.

20:13And I think a testament to the fact that like real businesses have been built in consumer AI already. No, to add to that, one of the surprises for me on companion was not seeing more multimodality. Yes. The kind of the first glimmers of that at scale were GROC. You know, GROC added a bunch of voices with some real aesthetics and points of you. You know. It's a good way to put it. But it's just interesting that that feels, and of course, characters got voice mode and more, but it feels like character is in companionship is such a horizontal category. There's so much latent demand and a really increase once you have multi -modality.

20:46The other interesting thing is that a lot of the text to code work, my assumption was that there was a small number of people who were creating sites that were heavily trafficked and that explained the rise of them. But actually, the majority of the traffic, correct me if I'm wrong here, Olivia, is from and people doing creation, not just consuming other people's creations. So this just, it really shows how much demand there is to make things, even if people are not that interested in consuming them. Yeah, you can track the traffic of like apps that people have launched on lovable .app versus visits to lovable .dev, which is where people go to make a lovable product.

21:21And like lovable .dev has more usage or more visits significantly than traffic to lovable .app, which gets back to what I was saying before. or like we have not even seen the first wave of viral products built on top of loveable and bold. And so when that happens, I think the awareness of these types of platforms is gonna go significantly up show. The app store is gonna be chaos. Yeah, I know. It's just gonna be chaos. We're gonna need an AI just to solve that AI app management problem. Completely. To that end, you talked about the fact that there are some consistent players. One of those players is Chatship T, which we've talked about as the starting gun of some of this application development.

22:00Chatubetit has been at the very top of the list. Has it been that way for a time? Single iteration of the AMOVAL. But maybe what would surprise people is that the traffic to Chatubetit hasn't always been the same trajectories. So maybe can you talk about that and what did we see this time around? So it was basically flat for a while, which I think was surprising to a lot of people between February 2023, basically for a whole year through February 2024. It was essentially flat in monthly visits to the website. And I think at that point, from the data that I've seen, basically 50 % plus of the traffic with students, who were using it for essays or homework problems, but the vast majority of other people, me included, to be honest, had not maybe found a daily active use case for CHGPT yet, and it's completely researched more recently.

22:48So they two x the number of visits on web since then. They actually made their own announcement to where they counted across Web and mobile. And in the past six months, they grew from 200 million to 400 million weekly active users. Wow. Which is especially surprising because it took them nine months to double before that. And it usually gets way harder to double at scale, not easier. I think from our perspective, if you even plotted on the graph, you can kind of track the increases to the release of new models that unlock new use cases. So like the new O1 reasoning models, the 4O models, which were multi -model for the first time and then advanced voice mode And then they've also launched new products like the operator that can perform tasks in your computer like canvas where you can write more naturally So it's both bringing in new users who never tried it and then taking people like me who Honestly, I was maybe a weekly if not the last a weird daily activity Yes, and now I'm a daily active but across several use cases now Some days I'm driving and talking to a voice mode.

23:51Some days I'm working on a memo and I'm generating something with the research. Some days I'm doing some random other project and I'm brainstorming ideas with it. So I would expect that to continue as they release new mods. Have you heard from the ecosystem in terms of what more frequent use cases have emerged like yours in terms of if before it was a lot of students writing research reports? Is there a sense of understanding of what those newer use cases are? Yeah, I think it's gotten better at some things related to coding. it's gotten better at data analysis. And then, I mean, the reasoning models, it's hard to overestimate because in the past, you couldn't even rely on Chatchee.

24:28We need to tell you how many hours were in strawberry. Accurately. So it was hard to feel good about really tasking any sort of delicate or serious work to it. And so I think there are probably a long tail of use cases that people have just migrated over and out of they have more confidence in the models. What's interesting to add to that is that quad is not a traditional number two player. Typically, the number two player has 10 % of the market share and 10 % of the product quality. And instead, Claude sits in this very interesting place where it seems like it's more beloved by a smaller number of people, it's better at creative writing, but it seems to have more of a personality, which is interesting because at least I think it's designed to be more constrained.

25:09And then it's also strangely much, much better at coding. Yes. Why? I don't know. but it's very interesting to see there's a place for both chat, GPT and quad and mistral and potentially other models, all to sort of augment each other. The really interesting thing about this list when it came to general LLM assistant usage was like, we only had 10 days of data for deep seek for January because it launched at the end of the month. And it shot up from literally nothing to number two on the list, 10 % of chat, GPT scale on web within a week, a little bit more than a week. On mobile, it had even less than that five days.