Baidu Releases ERNIE 5.5 Flash Base: A 280B MoE Model With 14B Active Parameters

Baidu has open-released ERNIE 5.5 Flash Base, a 280-billion parameter mixture-of-experts language model that activates 14 billion parameters per forward pass, targeting efficient large-scale inference for Chinese and multilingual applications. The model follows a similar sparse-activation design philosophy to other large MoE releases, allowing high-capacity reasoning at comparatively low serving cost. ERNIE 5.5 Flash Base is released as a base model, meaning developers will need to apply instruction tuning or RLHF fine-tuning for specific task alignment, making it most relevant for research teams and enterprises with custom fine-tuning pipelines. Its release adds to the rapidly growing pool of open large MoE models from non-Western labs, increasing competitive pressure on the open-weight frontier. Developers building multilingual or East Asian language applications now have an additional high-capacity open option to benchmark against.