Base44, the vibe coding platform acquired by Wix for $80 million just a year ago—when the company was barely six months old and had a team of eight—has begun rolling out its own AI model to help users build applications using natural language. This development comes amid growing debate in AI circles about whether frontier models are the best fit for every use case. A related question is whether businesses built on top of third-party models can truly sustain a competitive advantage over the long haul. Base44’s latest move, based in the Bay Area, speaks to both concerns. While its custom large language model (LLM) is only starting to roll out, Base44 hopes it will eventually outperform frontier models. According to founder Maor Shlomo, “training and owning the model as part of [our] entire stack allows us a lot more optimizations on latency, cost, and efficiency.”

EMBED_PLACEHOLDER_0

At first glance, this could be a strategy to stay ahead of competitors like Swedish startup Lovable, which achieved unicorn status during its Series A round last summer and relies on external LLMs. However, Shlomo expects that others will train their own models—“at least the players that have gotten enough scale and velocity to have enough data.”

According to Jonathan Userovici, a general partner at venture capital firm Headline—whose portfolio includes AI companies like Mistral AI, but not Base44—data is one of three key ingredients for defensibility in AI startups, alongside distribution and tech stack. The takeaway is that players with strong brands are now leaning into their data and infrastructure to boost defensibility, and Base44 fits that pattern. The company says the first version of its LLM, Base1, was developed and trained on a dataset generated from “tens of millions of real user interactions on the platform.”

EMBED_PLACEHOLDER_1

This dataset will continue to grow with the company, but so will those of its rivals. The bigger competition may not come from other vibe coding startups at all, but rather from frontier AI labs that are encroaching on Base44’s territory—Cursor and Grok’s parent company xAI now both belong to SpaceX, and Claude Code has become a vibe coding player in its own right. This gives Anthropic and other foundational AI providers access to data and feedback loops they can use to improve models for app creation, but Shlomo believes specialization gives Base44 an edge. “Models are progressing, but they’ll stay very general in what they can do,” he predicted. Userovici, for his part, warned against underestimating frontier models, citing the example of legal tech startup Harvey, which abandoned plans to train its own model. He doesn’t expect applied AI companies to become frontier labs en masse, but frames Base44’s move in a broader context—one where inference costs have become a significant part of the equation. That cost pressure, Userovici says, has driven changes that enterprise customers now demand. “They don’t necessarily see a [return on investment] when using the latest models for all use cases, so an entire infrastructure is being set up to do orchestration and optimization to select the right models for them so that costs don’t skyrocket while maintaining the same or similar performance across the majority of use cases.”

Enterprise companies still represent a minority among vibe coding platform users, but they account for a growing share of platform revenue, and users of all sizes are starting to express concerns about the cost of using AI. Base44’s decision to develop its own LLM stems from multiple factors, with cost reduction likely among the benefits. “We want to get a model that is going to be more aligned to what we think is the right thing, is going to be more optimized to what we see users like in terms of the results we’re getting, and is going to be faster and cheaper for customers eventually than using the frontier models like Opus,” Shlomo said. As for Base44 itself, cost reduction isn’t as straightforward. In a press release, the company explained that “ownership of the model gives Base44 direct control over compute and inference spend, expected to result in a structurally stronger margin profile over time.”

EMBED_PLACEHOLDER_2

Even with a delayed payoff, improved margins would be good news for Base44’s parent company, which recently announced it would lay off 20% of its workforce. In contrast, Base44 has been growing in headcount since the acquisition—and announced it had passed $100 million in annual recurring revenue a few months ago. That’s still less than Lovable, which said it hit $500 million in ARR earlier this month. But Shlomo is betting that the “huge engineering effort” to develop Base1 will cement Base44’s positioning as the “only vertically integrated vibe-coding application”—meaning, in Userovici’s terms, a player that owns its distribution, data, and infrastructure all at once.