Runway also could be, depending on who you ask, one of the most consequential AI companies today. Not because of what it has built, but because of what it is trying to build next.

For the past several years, the AI industry has largely operated on the premise that intelligence lives in language. Large language models like OpenAI’s ChatGPT and Anthropic’s Claude reflect that bet.

Runway, alongside other competitors, is making a different one. Its founders believe the next form of AI intelligence won’t be built from text, but from video and world models that learn how the world works, not just how humans describe it. That distinction sounds academic. Its implications are not.

Runway co-Founder and co-CEO Anastasis Germanidis said training models directly on observational data from the world is the next frontier of AI. The companies that get there first, he argues, won’t be the ones who perfected language.

“We’re basically bound by our own understanding of reality,” Germanidis told TechCrunch from Runway’s homey sunlight-filled headquarters near Union Square.  

“Language models are trained on the entire internet, on message boards and social media, on textbooks — distilling the existing human knowledge,” Germanidis continued. “But to get beyond that, we need to leverage less biased data.”

Founded in 2018, Runway built its reputation on video-generation models — including its latest Gen-4.5 — and AI tools that let people turn text prompts into editable, cinematic content.

Today, Runway’s technology powers production workflows for filmmakers and ad agencies, and the company has signed deals with major media players like Lionsgate and AMC Networks. Its tools have even been used in films such as “Everything Everywhere All At Once.”

Runway is now valued at $5.3 billion and, according to one of its founders, added $40 million in annual recurring revenue in the second quarter of 2026.

If Runway’s bet that video generation is the path to world models pays off, the result will be felt from Hollywood to drug discovery. If it doesn’t, Runway risks being outpaced by competitors with far deeper pockets — Google chief among them.

Taking the leap

Within the last six months, the startup has put its plan into action and expanded beyond video generation, launching its first world model in December, with plans to launch another this year. (World models are AI systems that simulate environments well enough to predict how they’ll behave.)

Runway isn’t alone in its pursuit of turning physics-aware video models to world models, with near-term use cases in interactive entertainment, gaming, and robotics training. Startups Luma and World Labs are on a similar trajectory, and Google has pointed its Genie world model in the same direction.

Everyone is after some version of the same thing: AI that solves humanity’s hardest problems. That’s far from Runway’s original product, but it’s the result of both emergent capabilities in the technology and founders who were predisposed to follow where it led.

For his part, Germanidis sees world models as scientific infrastructure. The more sensory data and observations you train a single model on, the closer you get to a working digital twin of the universe — one you can run experiments on faster than any lab could. Much of the scientific process is just waiting on results, he points out. If you could compress that waiting, you could compress progress itself.

“If we can build a better scientist than human scientists, we can accelerate progress in how we understand the universe and how we solve problems,” Germanidis said.

The moonshot

Germanidis fell in love with programming as an 11-year-old in Athens and came to the U.S. at 18 to study neuroscience and film. He turned back to computer science, working at several Silicon Valley tech firms before deciding he’d had enough of the culture. Co-CEO Cristóbal Valenzuela, born and raised in Santiago, studied economics as an undergraduate before working in film and then software. Another Santiago native, Chief Innovation Officer Alejandro Matamala-Ortiz studied advertising and ran a design firm.

The three met in 2016 while attending NYU’s ITP (Interactive Communications Program), a graduate program that Valenzuela described as an “art school for engineers.”

The co-founders had all aspired to be filmmakers at certain points in their lives, according to Matamala-Ortiz. So Runway started with a simple mission: Can we use AI to make everyone a filmmaker?

After releasing their first video generation model in February 2023 — which is staggeringly unimpressive compared to what Runway is putting out today — that mission evolved into: Could we make everyone a great filmmaker, according to Matamala-Ortiz.

It required growing the team to what it is today. The company has 155 workers spread across offices in New York, London, San Francisco, Seattle, Tel Aviv, and most recently, Tokyo. “But throughout this process, we learned that these models can understand how the world works, and if you scale them, they can be useful for many other different things,” he added.

Things like robotics, drug discovery, and climate modeling — the kinds of problems that have stumped researchers for decades. Last year, Runway launched a robotics unit which Germanidis says has already resulted in real-world testing and deployments.

Germanidis, like others, sees the field heading toward training a single model on many different modalities — text, video, voice, and other sensors — and thinks the compounding effect is the point.

His own moonshot goal for Runway’s technology, given enough time and resources, is biological world models and anti-aging research.

Whether Runway can carry its video dominance into world models is far from settled, and the competition isn’t waiting around. Runway was among the first to AI video generation, but world models are a different race with deep-pocketed and well-respected competitors. Google, former Meta chief scientist Yann LeCun, AI’s ‘godmother’ Fei-Fei Li, and a growing field of startups are all chasing the same goal.

Kian Katanforoosh, CEO of AI skills benchmarking company Workera and a lecturer at Stanford, pointed out that no one has yet proven the jump between video intelligence and generalized reasoning via world models, but that doesn’t mean it’s impossible. He said that if Runway wants to turn its world model bet into reality, it will need to continue gathering resources — compute chief among them.

Runway has deals with CoreWeave and Nvidia, but wouldn’t confirm whether it has dedicated cluster access — the kind of guaranteed, large-scale compute that training frontier models requires.

“How are you going to build a foundational model without a cluster?” Katanforoosh asked. “I don’t think anybody can do that.”

Runway has raised $860 million to date, including a $315 million round in February from strategic partners like AMD Ventures and Nvidia. That’s roughly in line with its most immediate competitors, Luma AI and World Labs, which have raised $900 million and $1.29 billion, respectively, according to PitchBook.

But Runway is also going up against incumbents like OpenAI, which has raised around $175 billion per CEO Sam Altman, and tech behemoth Google, whose parent company Alphabet is worth $4.86 trillion. Google is Runway’s biggest threat. The company’s Veo model competes directly with Runway’s video generation business, while its Genie world model targets the same longer-term territory Runway is racing towards.

Katanforoosh nodded at OpenAI, which shuttered its video platform Sora in March after burning roughly $1 million per day in compute costs with barely $2.1 million in revenue according to some estimates. His point: resources alone don’t guarantee survival. They don’t guarantee it for Runway either.

Katanforoosh isn’t writing Runway off. He pointed to AI audio startup ElevenLabs, which has outperformed OpenAI and Google on their own benchmarks, despite lacking the resources and pedigree of either. Runway, he argues, could follow a similar playbook.

The comparison isn’t lost on Runway’s founders. Valenzuela says the startup’s lack of Bay Area “standardization” gives them an edge. Not only do they have diversity of thought, he contends, but without Silicon Valley ties, they had to be scrappier, lacking the war chest many of their peers have access to that would have insulated them from the need to generate revenue early.

And according to Michelle Kwon, Runway’s chief operating officer, the company isn’t in a rush to raise more funds, even as compute demands increase with scale.

“Their background has led them to be early, to be right more often than not, and to build a culture that moves incredibly quickly,” early investor Michael Dempsey, managing partner at Compound, told TechCrunch. 

For Valenzuela, that culture starts with how he sees the world in the first place. He spends whatever free time he has — not much, as a co-CEO and new father — reading books, including the Chilean poet Nicanor Parra, whom he describes as the antithesis of Pablo Neruda: less formal, less academic, holding a view that poetry belongs to the people rather than to rules.

“Rules are just rules they invented,” Valenzuela said. “That’s a driving force of how we do things at Runway. They say Silicon Valley is here and that’s where the startups are. Why? Those are just made up rules. Scrub them all and start again.”