Meta is preparing a new AI model, Watermelon, which has reportedly caught up with GPT-5.5.
Meta AI Director Alexander Wang said that the company's upcoming AI model, codenamed Watermelon, has caught up with OpenAI's flagship GPT-5.5 model.
Meta AI Director Alexander Wang said that the company's upcoming AI model, codenamed Watermelon, has caught up with OpenAI's flagship GPT-5.5 model.
Wang based his statement during an internal company meeting on the results of popular benchmarks for AI models. However, it is currently unclear which tests he was referring to, Business Insider reports .
According to sources, Wang said, “Watermelon, our next model after Avocado, is currently being trained.” He also added that Watermelon uses an order of magnitude more computing resources than Avocado — referring to the Muse Spark model that Meta released in April .
Wang has hinted at this progress publicly. On Thursday, in a post on X, he noted that an update to the current Muse Spark model will be released soon. It will bring significant improvements to the coding and operation of AI agents, aimed at closing the gap with competing models.
When one user asked when Meta would have a model for coding the level of Claude Opus from Anthropic, Wang replied that it would be "pretty soon," adding that users would love what the company is "cooking up" right now.
Meta’s AI ambitions have long been centered around one simple goal: to catch up with OpenAI, Google, and Anthropic. But despite spending a ton of money on chips, data centers, and top talent, the company has struggled to convince developers and customers that its models are truly top-tier.
But if Wang is right, it’s the clearest signal yet: Meta’s billion-dollar investment and Zuckerberg’s aggressive talent hunt are finally paying off, even as the tech race continues to accelerate.
The company plans to spend between $125 billion and $145 billion on chips, data centers and other infrastructure this year, up from its previous forecast of between $115 billion and $135 billion. The company cited rising component costs and additional capital spending on data centers as the main reasons for the increase in spending.
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