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

Baidu has released ERNIE 5.5 Flash Base, a 280B-parameter text-only sparse MoE pre-training checkpoint that activates 14B parameters per token, with 128K training context and up to 1M for fine-tuning and inference. It uses hybrid attention (37 HCA layers caching 1 entry per 128 tokens plus 6 MLA+DSA layers), 512 routed experts with top-10 plus one shared expert, and ECHO in place of MTP, and was pre-trained from scratch on 33.5T tokens with the Muon optimizer. Baidu reports best scores on 24 of 30 base-model benchmarks in its unified pipeline, including MMLU-Pro 78.4 versus 69.2 for DeepSeek-V4-Flash-Base, with weights on Hugging Face and ModelScope in FP8 and BF16 and serving documented for SGLang and vLLM.