Muse Wonder Puts Meta Back at the AI Frontier

Meta released two new AI models, Muse Wonder and Muse Wonder Full, which the company says place it back at the frontier of AI development, with Muse Wonder Full ranking just below Anthropic's Claude Opus 5.5 and above Claude Fable 5.1 on the Artificial Analysis Intelligence Index. Meta says the largest version outperforms OpenAI's GPT-6 Astra and both Claude models on some specialized benchmarks, including legal-document work and software building, and the models will be available through an API and the Muse Code software tool. The release follows Mark Zuckerberg's overhaul of Meta's AI research into Meta Superintelligence Labs, led by former Scale AI CEO Alexandr Wang, after the Llama series fell behind Anthropic, OpenAI, and Google.

When Mark Zuckerberg https://www.wired.com/tag/mark-zuckerberg/ rebooted his company’s artificial intelligence efforts last year, it seemed to be a very expensive https://www.wired.com/story/mark-zuckerberg-meta-offer-top-ai-talent-300-million/ gamble. Meta’s latest AI models, Muse Wonder and Muse Wonder Full, seem to show that the bet is finally paying off by putting the company back at the frontier of AI development. Muse Wonder Full boasts frontier capabilities, Meta says, meaning that it is among the most capable AI models in the world. “Together, they mark the next step on our scaling ladder and a major leap toward personal superintelligence,” the company said in a blog post https://research.meta.ai/blog/introducing-muse-wonder today. The Muse Wonder models will be available though an API and through Muse Code, a tool for writing software with AI. Meta says the best version of the model will power features across its platforms, including its Muse personal agent https://www.wired.com/story/ai-agents-dots-devday-muse-battling-it-out/ . Zuckerberg overhauled his company’s AI research last year by sinking billions https://www.wired.com/story/mark-zuckerberg-meta-offer-top-ai-talent-300-million/ into the recently formed Meta Superintelligence Labs, and hiring the former Scale AI CEO Alexandr Wang to lead it. This effort has sometimes been rocky https://www.wired.com/story/researchers-leave-meta-superintelligence-labs-openai/ , with some researchers not sticking around for long. Meta was once a trailblazer in AI. Its Llama series of models https://www.wired.com/story/metas-open-source-llama-upsets-the-ai-horse-race/ were the first frontier open-weight offerings from a big lab. Llama, which could be downloaded and run on one’s own hardware, was widely adopted by researchers and startups. But the company fell behind after delivering several disappointing versions of the model, and as Anthropic, OpenAI, and Google rapidly introduced more capable models. Meta announced the first model from its new lab, Muse Spark https://www.wired.me/story/metas-new-ai-model-gives-mark-zuckerberg-a-seat-at-the-big-kids-table , in April of this year. The company has also released a small open weight model called Muse Glimmer https://research.meta.ai/blog/introducing-muse-glimmer-open-agentic-model , and says it plans to release larger open-weight models in the future. It did not disclose details of how new Muse Wonder models were built or trained. Muse Wonder was built to compete with the very best, however. Meta says the largest version of the new model outperforms Anthropic’s second-best model, Claude Fable 5.1, and ranks just below its best, Claude Opus 5.5, on the Artificial Analysis Intelligence Index https://artificialanalysis.ai/evaluations/artificial-analysis-intelligence-index , a widely used aggregated score of model capabilities. Meta says the model outperforms OpenAI’s best model, GPT-6 Astra, and both Claude Fable 5.1 and Claude Opus 5.5 on some specialized benchmarks, including ones that measure a model’s ability to work with legal documents and to build software. Benchmarks are not always a reliable measure of real-world performance, but this is still a significant step forward for Meta’s models. Muse Wonder also includes two novel features designed to help make agents more effective and less inclined to misbehave. The new features, called Active Memory and Active Focus, are designed to keep the model locked into a stated goal, and prevent it from becoming confused. This can be a challenge when AI performs complex research or builds a large software project, for example, and can lead to expensive mistakes or compounded errors. Meta says it has put significant effort into training Muse Wonder to refuse to generate dangerous outputs, such as recipes for building bioweapons or help with hacking. It says the company scores well on several benchmarks designed to measure how resilient models are to those prompts. A series of recent incidents involving rogue AI agents https://www.wired.com/video/watch/rogue-anthropic-agent-submitted-fake-tip-in-unsolved-homicide-case from Anthropic, OpenAI, and others, also shows how easily powerful AI models can stray when given open-ended commands. Meta did not disclose whether it has seen agents powered by Muse Wonder misbehave in testing or what it has done to mitigate this issue specifically. Zuckerberg said in a post on X https://x.com/finkd/status/2099997096896274533 last month that the company had delayed the release of its Muse models to work on safety. Meta also revealed a framework https://research.meta.ai/blog/developing-capable-models-responsibly designed to ensure that it scales its models’ capabilities safely in a blog post earlier this month. Muse Wonder may add more fuel to an already furious race to develop more capable AI, however. It certainly suggests that Meta is once again competitive in the increasingly high-stakes AI race.