Catenaa, Thursday, July 09, 2026- Meta is rolling out a major update to its AI model as it attempts to compete with OpenAI and Anthropic in critical areas of the market.
Muse Spark 1.1, which Meta introduced on Thursday, represents its “strongest model for agentic and coding work yet,” Meta AI Chief Alexandr Wang said in an interview with CNBC.
The initial Muse Spark model released in April was only available to “select partners” who could access the technology via a “private API preview.”
Meta is making the new model’s API available through a developer portal as part of a public preview, where users will be able to sign up and see instructions for integration.
A Meta spokesperson said some early partners can already access the API, and new users “will be able to add themselves to a waitlist and be added from there over time.” For now, Meta said it’s limiting API access to its own properties rather than making it available on third-party platforms like the popular OpenRouter marketplace.
“This is going to be served on top of the computer infrastructure that we’ve built,” Wang said.
It’s Meta’s second notable rollout for the Muse family this week. On Tuesday, Meta released Muse Image, originally code-named Mango, a model for creating images, as the company seeks to attract creators and advertisers to its offerings.
Meta CEO Mark Zuckerberg is coming under pressure from Wall Street to show a return on the company’s massive and growing investment in AI infrastructure and development.
While it’s spending at the rate of its hyperscaler peers, Meta doesn’t have a cloud infrastructure business (though it plans to start one), and it’s failed to keep up with OpenAI, Anthropic and Google in developing popular models and AI applications.’
Wang characterized pricing of the Muse Spark update as “very aggressive and attractive” compared with similar offerings from labs like Anthropic and OpenAI. He said every new API account will start with $20 in free credits. From there, the company will charge $1.25 per million tokens in input, and $4.25 per million tokens of output, he said.
“The goal is to really have attractive pricing that scales with immense consumption usage,” Wang said.
He said Muse Spark 1.1 outperformed rival models in certain tasks involving the ability to interact with various third-party coding products and services.
Wang’s Meta Superintelligence Labs, or MSL, trained Muse Spark 1.1 to excel in coding-related tasks because that ultimately improves the capabilities of AI agents that can autonomously perform multiple tasks like a fleet of human interns, he said.
“You kind of have to build coding capabilities as part of that in service of overall agentic capabilities,” Wang said.
The tech industry’s excitement about AI agents took off in the first half of 2026, in part due to the sudden popularity of OpenClaw, which developers could use to manage AI models that power supercharged digital assistants.
Wang said Meta trained Muse Spark 1.1 “to be able to work well with all of the most popular harnesses that developers use today, and we felt that was the best approach for this model given our goal to maximize adoption.”
