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MiniMax-M2 proves that massive parameter counts don't always translate to better agentic performance; strategic activation of a smaller subset can unlock frontier-level intelligence.
LALMs can learn to strategically "think aloud" during spoken interactions, improving accuracy and reducing response latency by externalizing intermediate reasoning steps.
