20VC: $1BN ARR in 18 Months; The Untold Story of Higgsfield | Spending $4M Per Month on Models | Why Moats in AI are BS | Scaling a Content Team to 150 People with Alex Mashrabov

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch

Alex Mashrabov, CEO of Higgsfield, details the company's unprecedented journey to $1 billion in annualized revenue within just 18 months. He

Key takeaways

• Higgsfield reached $1 billion ARR in 18 months, outpacing Coursera's growth rate.
• The company spends over $4 million per month on internal AI model usage.

Main topics

• Higgsfield's hypergrowth
• Economics of AI model inference

Notable quotes

It actually took us 18 months from $1 million to $1 billion.

Conclusion

A masterclass in hyper-scaling a modern AI startup through product exc

Transcript preview

Speaker 1 (0:00) My parents told me that I must get to the United States because this is the place where technology matters. By the age of 19, I was able to get to top three in the world in competitive programming. Actually, it took us 18 months from $1 million to $1 billion. For Coursera, it took 24 months. On average, at Hicksfield, a person on the team spends over $10,000 a month on various models. So internal usage. of models a month is over 4 million. I just caught a guy who spent over 30k in a week on Astra model. Many people spend over 10,000 in a week. Higgsfield. This is the story that no Speaker 2 (0:39) one has told in startups yet. The company has just hit a billion dollars in revenue. It is the fastest growing company in consumer land to hit this milestone. It even surpassed Cursa. And guess what? The travesty. No one has covered this story. This company is built with 300 people out of Kazakhstan. It is a complete anomaly and you don't know about it. Alex, the founder, is an incredible genius, one of like the most talented computer programmers competing in competitions from a like super, super early age, and then building a company that he sold to Snap for over $160 million. Now, Higgs field, rumored to be raising at an $8 billion price, has just crossed a billion in revenue. This is the story that you don't know that you need to know. But before we dive into the show today, founders face a different set of challenges at every stage of growth. For Sid Shate, co-founder and CEO of D-Matrix, J.P. Morgan delivered the guidance and expertise to help navigate what came next. He credits J.P. Morgan's high-touch approach with supporting D-Matrix as it grew and expanded internationally. Whether you're in the early days or expanding into new markets, J.P. Morgan helps startups navigate complexity with real confidence, offering personalized guidance and deep sector expertise. Find out how J.P. Morgan helps. founders at jpmorgan.com forward slash grow without limits. JPMorgan is the bank of the innovation economy. While Speaker 1 (2:11) JPMorgan Speaker 2 (2:12) supports growth, Corgi protects it. My word, what an arresting first line. Get your ass covered with Corgi insurance, and I'll tell you why. If you're running a business right now, you already know this pain all too well. Getting insurance, it's really slow, it's confusing, and my word, it's full of paperwork. Well, that's exactly why Corgi is here to change the game. Corgi is the first and only insurance carrier designed specifically for tech companies, allowing you to get covered in minutes instead of days. Corgi provides essential coverages for all growth stages, such as... D &O, E &O liability, cyber, commercial, general liability, and more. Get your ass covered. I love the way we say ass with Corgi Insurance alongside thousands of other startups at corgi.com forward slash 20VC today. That's corgi.com forward slash 20VC. You won't regret it. While Corgi covers risk, Flex gives you room to move. Business owners run their whole financial life on Flex. One platform from business revenue to their personal spend. Float every purchase for 60 days. Tap capital that grows with your revenue and pay vendors in 170 countries across 32 currencies. Plus the whole back office. Bills, expenses, accounting, all in one place. So you spend less time reconciling and more time growing. That's why thousands of owners use Flex, named one of Fast Company's most innovative companies of 2026. Visit flex.one, that's F-L-E-X dot O-N-E, and use the code 20VC. You have now arrived at your destination. Alex, I am so excited for this, dude. We were talking downstairs and I said, I don't think the Higgs field journey has been told before. And it's an amazing journey. So thank you so much for joining me today. Speaker 1 (4:04) That's a very special opportunity for us. Thank you for having me. Obviously, your story is inspiring as well, like how social media has become like an elevator for your opportunity to create fun and so on. It's Speaker 2 (4:15) very Speaker 1 (4:15) kind of you to say. I do just want to Speaker 2 (4:17) go back though, because you're not the Stanford Silicon Valley born and bred engineer. You were a competitive programmer in Kazakhstan. Can you just take me back? How did you first find and fall in love with computers Speaker 1 (4:32) and become a programmer so early? So first, you need to understand where I come from. So my father is from Uzbekistan. Uzbekistan is a country in Central Asia where if a family of five people makes $1,000 a month, it's considered to be wealthy. It's like not very high standards of living, unfortunately. But both my parents are professors of mechanical engineering. And since I remember myself, since I was eight, my parents told me that I must get to the United States because this is the place where technology matters. So mother had to work three jobs because basically my education was to compete in programming competitions all the time and to go to various educational camps. where I could learn from the best, like certain data structures, algorithms, and so on. Can Speaker 2 (5:20) I ask you a question? Did you feel pressure as a child competing, being pushed into these environments Speaker 1 (5:27) when you are so young? Absolutely. And I'm very grateful to my parents that they showed me the path really from that early on. Definitely when you come from this part of the world, think about post-Soviet countries, India, China, like getting to the top. of the rankings in any competition, in any international competition is the only way to really break out. So by the age of 19, I was able to get to top three in the world in competitive programming. But then instead of pursuing like an academical career, I decided to do startups. Speaker 2 (6:00) I'm sure your parents were thrilled. Can you take me to that decision? This is like the penultimate moment. You've worked 19 years for your parents have told you this is like the mother load. This is the thing. And you're like, I'm going to go and do this really risky thing Speaker 1 (6:15) called a startup at this point. What happens then? So let me take you back to 2014. I was very fortunate to work on pre-transformer architecture neural nets. And that was primarily just... doing optimization, make it run faster, parallel across multiple machines and so on. And we actually built state of the art system for language translation from English to Russian and Russian to English. Apparently, talent wars were a real thing even back then. A lot of my teammates were hired by DeepMind and Meta. But my passion was actually different. I was very, very surprised to learn when I come to SF for the first time how quickly Uber actually spread out. And I was thinking, if this app can take over the world so quickly and transform the whole industry, maybe what's going to happen is that mobile phones are going to become the most used devices in the world. Maybe there is going to be a version of the future where everyone is going to be spending most of their time in their life watching AI-generated videos on the phones. Because who else is going to produce videos for the phones? Maybe it's going to happen with AI. Okay. And Speaker 2 (7:19) so that was the company that we built before that you sold to Snap? Speaker 1 (7:23) So yeah, so the company was called AFactory. Was fortunate to meet Mahi 2018. He's co-founder of Hicksfield. And he's like a veteran of Silicon Valley, went through ups and downs and sold it to Snap for 166 million. Then I was leading Gen EI there. Pause. Speaker 2 (7:41) No offense, dude. You come from a family of incredibly ambitious parents who push you to do well. And you just skip to the moment where you sell for 166 million. It's a lot of money. How did that feel when you did it? We Speaker 1 (7:55) both remember these times where the capital for AI companies was not really that much available. And AI multiples were not like 200 to revenue as they are today, but closer to zero because AI was not a topic. So there was like severe dilution, which we experienced. So just to calibrate. But what was around? No, look, I mean, back then, rounds of like one, two million dollars, having like one, two million dollars in investments was considered to be really good. But it was still an opportunity for me to finally go to the United States. So after the acquisition, I permanently moved to first to LA and then to Silicon Valley. And my dream simply came true. Was Speaker 2 (8:34) it what you thought it would be? Speaker 1 (8:35) That's Speaker 2 (8:36) a Speaker 1 (8:36) good question. So San Francisco is definitely a place where no one judges by race, nationality, and so on. That's truly phenomenal. There is definitely a meritocracy in a sense that it's possible to meet anyone. But in the same time, what I see across Silicon Valley investors, it's extremely consensus driven. I think that last part I expected to be different. But then I read the book about the law of capital and I realized this is just how the world works. So then we have Speaker 2 (9:05) sold to Snap. We're now in the US. This is the moment you wanted. How does Hicksville come to be? Back Speaker 1 (9:12) then, Like Snapchat 2020 was really growing so quickly. And the face filters, which my team has built, was driving most of daily new users. What's important is that these face filters, we were able to manage to run on mobile devices. So it was virtually for free for Snapchat. It's not like current LLM tokens costs. And it scaled to hundreds of millions of people throughout the world. And it was truly phenomenal to me to build a product, which is still probably the most used consumer media product. But then what? I realized is that there are a lot of unmet needs on advertising sites. Average company cannot figure out how to be relevant on social media. And this is a major gap. Like social media is the main media in the world. A lot of companies are actually able to build direct response advertising so that they can actually sell more. But in the same time, most of the companies in the world cannot simply do that. And basically, because no one simply can keep up with the pace of production for social media as trends change pretty much every day. And Speaker 2 (10:15) so you were like, hang on a minute. These big brands aren't able to have media houses. And so we need to create a tool that lets them. That was the sound? Speaker 1 (10:23) Yeah, absolutely. So where it all really started is that there was a tool like to upload set of images and transform them into a slideshow with music. It's kind of better than nothing, but still pretty bad, right? Another solution was to take long form video and cut them to short vertically oriented videos. This was better, but still really not perfect. And it felt to me that, especially 2023, it was absolutely clear that scaling loss finally work. It's not just a concept from science that scaling loss work. Video just takes maybe two or three years longer than LLMs and coding. But it was clear that finally scaling loss should work in video as well. And I just decided just to take a bet. But I just want to go back. I get Speaker 2 (11:07) that in terms of what we see, which is, hey, we want to empower these brands and companies to create amazing media for social media. But it wasn't a hit from day one. And I spoke to Amy at Menlo, who mentioned like a couple of pivots before and the meandering that we had. So what happened when we launched? Did we have immediate product market fit? Speaker 1 (11:26) No, actually, we spent more than a year in a search of a product which could work. We burned more than 10 million out of 16 million raised in seed fundraising. So we felt we have just one attempt left. And frankly, I feel I am responsible because I was focusing on the wrong things. I think I just lost the touch with reality back then. I was so much optimizing for what's hype today, what's the right narrative, how we can hijack the attention, all these things, really. Everything instead of building a good product. So when we had... less than 6 million left. I guess it was slightly less than five, actually. I realized that the only thing which we can be focused on is to lean into the product, PLG, and just finally set belief that the best product is going to win. And then we just started to talk to customers. We spoke to eight creative directors about their experience with AI and what's simply missing. Everyone told us that camera control does not exist in AI. And camera control is so important to tell a story. So this is a very important bottleneck to solve. So we released our products March 31st last year. And since then, we are really riding this crazy wave. Was it immediate product market fit then? Like, yeah, it was immediate. Is product market Speaker 2 (12:52) fit like love? When you know, you know. Speaker 1 (12:55) Yes, it's definitely when you know, you know. Like, for example, we don't do any paid. And like we have on the team, people who scaled businesses to over like... billion and two billion in revenue like other businesses with paid advertising. At Hicksfield, we decided to really make a bet that- Speaker 2 (13:12) You Speaker 1 (13:12) don't do paid? We don't do paid. Is influencers not paid? That's a good point. So with influencers, there is typically, there are different types of influencers, but typically there is some fee for just video production and then like some cost per click like attribution, which is like works really well on YouTube. Speaker 2 (13:32) You guys. Got into some controversy for like, I can't remember what it was. You were like paying people to promote for you or doing something rogue with influencers. Was that completely unfair? Was it kind of my bad we did do that? How do you respond to that? Speaker 1 (13:52) Look, I think the main takeaway from our experience is that it's very important to own distribution. Distribution now more important than ever. And we basically did outsource. We had just a team of two people on creator and customer success sides. And we just did outsource to the agency. And that was not a good experience. I do just want to go back to part of the story. Where are you at revenue-wise Speaker 2 (14:17) today? Speaker 1 (14:18) So today is actually an exciting day. When we recorded, just Bloomberg article went out so that we crossed $1 billion in annualized revenue. Speaker 2 (14:27) If I had a gong here, I'd be hitting the gong. A billion in revenue. Speaker 1 (14:31) Yes. Actually, it took us 18 months from $1 million to $1 billion. For Coursera, it took 24 months. So we are probably like the third after OpenAI and Anthropic. 18 months Speaker 2 (14:47) from a million to a billion? Yes. How do you calculate revenue? It's a controversial topic. How do you Speaker 1 (14:55) calculate revenue? Absolutely. By the way, your co-host Jason also asked this question in May. Luckily, the answer didn't change. So we are at least consistent. So let me be transparent on that. What we do is we look revenue over the last four weeks and multiply it by 13. from what I know, OpenAI, Anthropy, Cloudable, all of them use the same methodology. What's very important is that we take revenue, not sales. So if that's like annual subscription or annual enterprise contracts, we prorate this across 12 months and only take a piece which corresponds to one month, to 28 days to be precise. That's the first piece. And second, it's only live revenue. It's only live revenue. We are not taking like three year enterprise deals and baking into like one billion figure. No, we don't do that. If you were to break that billion up today Speaker 2 (15:47) into annual contracts, monthly subscriptions, and then token spend, what would that be? Speaker 1 (15:54) So video AI is still relatively early. It is still probably two years behind coding in terms of adoption. So on-demand usage for leading... Coding companies could be over 50%. And I would be honest for video, it's substantially less than that. In the same time, what's very interesting for us to observe in the business is that there is significant revenue expansion. I always love to study stories of the largest customers on the platform. So one customer started six months ago, spending just subscription $99 a month, $99 a month. And now we just signed a deal over 6 million. 6 million? 6 million a year, right? So this level of acceleration is something which really mind blowing to me. Dude, Speaker 2 (16:45) what are they getting for 6 million a year? That's like a Hollywood content team almost. Speaker 1 (16:51) So there are multiple trends and all of them, frankly, coming from Asia. So first, we're seeing a lot of direct-to-consumer e-commerce companies rebuilding their whole go-to-market to be AI native, where they just make hundreds of ads, if not thousands a week, where they can A-B test what performs well. But we all know about short-form dramas, right? Short-form dramas today is an industry over $10 billion. owned primarily by Chinese companies having huge impact both in China, United States and Europe, everywhere in the world. And most of new shows there are made with AI end to end. So look, I think this adoption obviously is coming like bottom up, but that's very difficult to refute this new reality. What Speaker 2 (17:38) percent of revenue is consumer versus enterprise? Speaker 1 (17:41) So that's a great question. So business revenue is slightly over 50%. Wow. Yeah. On the consumer side, it's also very important to