30-06-2025
- Business
- South China Morning Post
Baidu the latest to join open-source movement with Ernie 4.5 models publicly available
Chinese tech giant Baidu on Monday marked its entry into the highly competitive field of Chinese open-source artificial intelligence (AI) systems, by making its flagship Ernie 4.5 models available for download on AI site Hugging Face.
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Baidu open-sourced 10 variants from its Ernie 4.5 multimodal model family, from the 0.3 billion parameter lightweight models to the heavyweight 424 billion parameter ones, according to a statement.
Beijing-based Baidu, one of the earliest tech firms in China to develop large language models (LLMs) following the release of ChatGPT in November 2022, has made a U-turn by making its models open-source. A year ago, founder and CEO Robin Li Yanhong was publicly saying its Ernie series, like OpenAI's ChatGPT models, would be more powerful than open-source ones.
However, the release of open-source models by Chinese start-up DeepSeek, which took the AI world by storm at the start of this year, triggered an accelerated shift to open-source by China's Big Tech firms. For example,
the Qwen models developed by Alibaba Group Holding are the world's most popular open-source models among developers. Alibaba owns the South China Morning Post.
The logo of Baidu's Ernie Bot is displayed near a screen showing the Baidu logo, in this illustration picture taken June 28, 2023. Photo: Reuters
Citing a range of benchmark tests that value an AI system's general and domain knowledge, coding and maths skills, as well as reasoning capabilities, Baidu said that its 300B Ernie 4.5 model outperformed DeepSeek's V3, which was twice the size of the Ernie model.
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The benchmark results showcase the progress Baidu has made in improving its models in recent months, after the company announced earlier this year it would shift to an open source approach. The move followed Hangzhou-based DeepSeek's emergence into the global spotlight with its open-source V3 and R1 models that were built cost-efficiently for high-performance tasks.
