Baidu has released ERNIE 5.5 Flash Base, a new open-source foundation model featuring 280 billion parameters. The Chinese company launched the model deliberately without fine-tuning or post-training, leaving developers to decide its direction, while a post-trained version is planned to follow.
The ERNIE 5.5 model utilizes a mixture-of-experts architecture with 280 billion total parameters, where 14 billion are active per input. It was pre-trained on 33.5 trillion tokens with a training context of up to 128,000 tokens, and is designed to support a context window of up to one million tokens during fine-tuning and inference. According to Baidu, the model competes with similarly sized open foundation models like DeepSeek V4 Flash and MiMo V2.5 in reasoning, code, and long-context benchmarks, with weights now available on Hugging Face in FP8 and BF16 formats.
This release matters because it provides developers with a large-scale open-source foundation model and mixture-of-experts architecture for customizable fine-tuning and long-context applications.