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Meta claims new Muse Wonder AI models rival OpenAI, Anthropic

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Meta unveiled two new artificial intelligence models, Muse Wonder and Muse Wonder Full, calling them its most capable models to date and a step toward “personal superintelligence.” The announcement on Monday places the company in direct competition with OpenAI and Anthropic. Meta co-founder Mark Zuckerberg said the newest models advance that personal superintelligence goal.

The models introduce two capabilities Meta calls Active Memory and Active Focus. Active Memory carries relevant information across conversations. Active Focus helps the agent sustain work on difficult tasks. Together, Meta says, these features make the models more useful for long-running, complex work.

Independent evaluation platform Artificial Analysis scored Wonder Full at 56 on its Intelligence Index and the standard Wonder at 52, both at maximum reasoning effort. That puts Full above Claude Fable 5.1 and GPT-6 Astra, which each scored 53. It remains below Claude Opus 5.5’s 58.

Bindu Reddy, CEO of Abacus.AI, challenged the performance claims. Writing on X, she said Muse Wonder was “nowhere near Fable or Astra level.” She added that detailed benchmark results would follow.

Meta’s new models are its most expensive to date. The standard Wonder model charges $4 per million input tokens, matching Claude Opus 5.5 but undercutting GPT-6 Astra and Claude Fable 5.1, which charge $10 and $50 respectively. Wonder Full is available only to Muse Code subscribers.

Those subscribers must choose the $50 a month “power usage” tier or the $200 a month “maximum usage” tier. The pricing signals Meta’s push into premium AI services. It also raises questions about whether developers will pay for unverified performance.

The launch intensifies competition among Meta, OpenAI and Anthropic. Independent evaluations and third-party benchmarks will shape adoption. If Muse Wonder’s performance holds up, Meta could gain share in enterprise and developer markets.

Read original article →Source: cointelegraph