A large mixture-of-experts model that activates only 3 billion parameters per forward pass despite its 80B total capacity, making it surprisingly efficient at inference time. It operates in a 'thinking' mode, working through reasoning chains before producing answers — which means it tends to be deliberate and thorough on complex problems but slower than non-thinking counterparts. The sparse activation pattern gives it broad knowledge coverage while keeping compute costs manageable.