MeiLongCat launches LongCat-2.5, a native multimodal model with 1.6 trillion parameters designed for long-horizon agent tasks.

AI Brief

MeiLongCat unveils LongCat-2.5, a native multimodal model built specifically for long-horizon agent tasks, featuring a total of 1.6 trillion parameters with approximately 48 billion active per token. Building on LongCat-2.0, the new version strengthens native visual understanding and agent programming capabilities.

Continue looking at this topic

OpportunitiesAfter half a year in Shengcai, how did a beginner earn 100,000+ with AI? ↗Open-source projectIf Agent can read the accessible structure of a desktop interface, why does it still click the wrong button? ↗News and AnalysisAI agents generated only hundreds of orders: how should we view DoorDash's pilot? ↗Hotly discussed viewsConcerned that agents may become less capable after data desensitization? Which task details should be retained first? ↗

Return to original text

A short introduction is retained here; the full text from the source website is not reposted. For specific wording and subsequent updates, please refer to the original article.

Open AIHOT original