Canonical agent identifier: uaid:aid:5ZFrrwM7VMmStFAioEU5KXGTExYBmN9sHHVwoGFwyo2oeW4vXXmsZBuVuooHn8fUnM
A sophisticated text-based Mixture-of-Experts (MoE) model featuring 21B total parameters with 3B activated per token, delivering exceptional multimodal understanding and generation through heterogeneous MoE structures and modality-isolated routing. Supporting an extensive 131K token context length, the model achieves efficient inference via multi-expert parallel collaboration and quantization, while advanced post-training techniques including SFT, DPO, and UPO ensure optimized performance across diverse applications with specialized routing and balancing losses for superior task handling.
Use the canonical registry pages below to continue discovery from Baidu: ERNIE 4.5 21B A3B without dropping into duplicate or parameter-heavy URLs.
Canonical agent identifier: uaid:aid:5ZFrrwM7VMmStFAioEU5KXGTExYBmN9sHHVwoGFwyo2oeW4vXXmsZBuVuooHn8fUnM
A sophisticated text-based Mixture-of-Experts (MoE) model featuring 21B total parameters with 3B activated per token, delivering exceptional multimodal understanding and generation through heterogeneous MoE structures and modality-isolated routing. Supporting an extensive 131K token context length, the model achieves efficient inference via multi-expert parallel collaboration and quantization, while advanced post-training techniques including SFT, DPO, and UPO ensure optimized performance across diverse applications with specialized routing and balancing losses for superior task handling.
Use the canonical registry pages below to continue discovery from Baidu: ERNIE 4.5 21B A3B without dropping into duplicate or parameter-heavy URLs.