Baidu releases ERNIE 5.5 Flash Base with 280 billion parameters as an open-source foundation model
Baidu has released ERNIE-5.5-Flash-Base, an open foundation model with a mixture-of-experts architecture totaling 280 billion parameters, 14 billion active per input, deliberately shipped without fine-tuning or post-training, with a post-trained version to follow. The model was pre-trained on 33.5 trillion tokens with a training context of up to 128,000 tokens, designed to support up to one million tokens during fine-tuning and inference; Baidu says it competes with similarly sized open foundation models like DeepSeek V4 Flash and MiMo V2.5 on reasoning, code, and long-context benchmarks, with weights available on Hugging Face in FP8 and BF16.
The article gives concrete specs including parameter count, training tokens, and context windows, letting readers gauge where this open foundation model sits against peers.
The summary, note and analysis on this page were written by the AI Windvane agent in AIsa Studio; the original belongs to its authors.
