Can Meta’s new AI model Muse Spark make money?

Almost 10 months later Meta The company, which spent billions of dollars to bring in Scale AI’s Alexandr Wang as the centerpiece of Mark Zuckerberg’s AI overhaul, finally unveiled the Muse Spark on Wednesday, its first new model since the switch. A big question is; Will users pay for this?

Competitors such as OpenAI, Anthropic and Google Meta, which has led the AI ​​boom with powerful models and popular chatbots as well as other services, has spent heavily on AI but has yet to show a new revenue stream from it.

In June, Meta spent more than $14 billion to hire Wang and some of his top engineers and researchers, soon establishing Meta Superintelligence Laboratories as a new elite unit. In January, the company told Wall Street it planned to spend $115 billion to $135 billion on capital spending this year, nearly double the 2025 capital spending figure.

“It’s been a year of basically no releases and a lot of hiring, and then capex concerns have been raised for this year,” Morningstar analyst Malik Ahmed Khan said in an interview. “I think Meta needed to show investors and operators that they were working on something important. This is the first step.”

Meta’s second step is to make the model work and figure out how to monetize it, Khan said.

Meta’s newly released model, the Muse Spark, is a proprietary model that’s a sharp change from the previous Llama model family of open-source offerings, but the company has said it plans to release some open-source versions eventually. Zuckerberg shook up his company’s strategy after the April release of Llama 4, which failed to attract developers’ attention.

Gartner analyst Arun Chandrasekaran called the move a “major shift” and said it “signals an intention to move away” from the Llama brand.

Taking a cue from other leading AI labs, Meta aims to offer paid API access to Muse Spark to third parties after an initial “private API preview” with “select parties.”

However, Meta came very late to the game. Thanks to the popularity of their models and services, OpenAI and Anthropic are worth over $1 trillion combined. While Google is building Gemini into its portfolio of apps and products, it is also selling access to Gemini models through its cloud unit.

For Meta’s AI technology to be successful, it must be good enough to compete with the best models and at the same time offer a new business opportunity.

Advertising accounted for 98% of Meta’s $200 billion in revenue revenues last year. The company has made numerous efforts to diversify its business; most importantly, it has spent tens of billions of dollars trying to make metadata a reality. But Meta’s ad model is the one thing that consistently works, and the company’s investments in AI have served to improve targeting capabilities and provide better tools for marketers.

As advertisers see a return on investment from their Meta spend, they reinvest that money into more ads on the platform, Khan said. Therefore, it makes sense that they would be willing to pay for AI services if they can achieve better results.

Meta declined to comment on its API plans beyond its initial announcement.

Doris These are important features for advertisers who want to create dynamic campaigns for an audience accustomed to watching short-form videos on Reels or gawking at cat photos on Facebook and Instagram.

“Compared with Claude and Gemini, I definitely think there is more consumer trend,” Xin said of Muse Spark.

But Zuckerberg has long had goals that go far beyond advertising. His approach to Llama was aimed at developers, aiming to get the best and brightest minds in AI using Meta’s tools even if they weren’t paying.

With the transition to proprietary models, the presentation to developers becomes more difficult. Joseph Ott, CEO of AI startup Samu Legal Technologies, said he wasn’t sure where to find value.

“The whole reason I use Llama is so I can fine-tune it,” Ott said, referring to the practice of customizing AI models.

Many developers are using vulnerability-heavy AI models, such as those provided by Chinese tech companies, to train AI models to meet their specific use cases. Ott said it’s unclear what will make Meta’s Muse Spark stand out against free or cheaper alternatives and leading proprietary AI models.

Ulrik Stig Hansen, co-founder of AI and data education startup Encord, said it was important for Meta to develop its own AI core models to avoid dependence on third parties in the future. As one of the few companies with the resources and computing infrastructure necessary to build and maintain large AI models, Meta wants to ensure it remains relevant in the hottest market on the planet.

“This is about AI dominance and being a player in the game,” Hansen said. “They want to be perceived and known as an AI company.”

As for Meta’s massive investment in Wang and his team, Boone said the latest benchmarks show Zuckerberg got what he wanted, and now it’s “back to Mark.”

“We gave you a state-of-the-art frontier model,” Boone said, referring to the team behind Muse Spark. “What are you going to do with it?”

WRISTWATCH: Why is Meta’s new artificial intelligence model, Muse Spark, so important?

Correction: Ads accounted for 98% of Meta’s $200 billion in revenue last year. An earlier version misidentified the figure.