Yuan3.0Flash: Open-source Multimodal Foundation Model Leading the New Wave of AI

Recently, the YuanLab.ai team officially released the open-source Yuan3.0Flash multimodal foundation model, which will bring new opportunities to the AI field. The model includes 16-bit and 4-bit model weights, as well as detailed technical reports and training methods, supporting community secondary development and industry customization, greatly promoting the popularization of AI technology.

The parameter scale of Yuan3.0Flash reaches 40B, and it adopts an innovative sparse mixture-of-experts (MoE) architecture. During inference, only about 3.7B parameters are activated. This design not only improves the accuracy of inference but also significantly reduces computing power consumption, embodying the concept of "less computing power, higher intelligence." In addition, the model introduces a reinforcement learning training method (RAPO), and through a reflection-inhibiting reward mechanism (RIRM), it effectively guides the model to reduce ineffective reflection, further improving performance.

In terms of structure, Yuan3.0Flash consists of a visual encoder, a language backbone network, and a multimodal alignment module. The language backbone network adopts a local filtering enhanced attention structure (LFA) and a mixture-of-experts structure (MoE), ensuring attention accuracy while significantly reducing computing power consumption during training and inference. The visual encoder can convert visual signals into tokens, which are input together with language tokens, thus achieving efficient cross-modal feature alignment.

In practical applications, Yuan3.0Flash has surpassed GPT-5.1 in enterprise scenarios, especially in tasks such as RAG (ChatRAG), multimodal retrieval (Docmatix), and multimodal table understanding (MMTab), demonstrating significant capability advantages. In multimodal and language reasoning evaluations, the model's accuracy is close to larger-scale models such as Qwen3-VL235B-A22B (235B) and DeepSeek-R1-0528 (671B), but its token consumption is only 1/4 to 1/2 of the latter, effectively reducing costs for enterprises using large models.

In the future, the source Yuan3.0 will release multiple versions, including Flash, Pro, and Ultra, with parameter scales ranging from 40B, 200B, to 1T, further enriching the possibilities of AI model applications.

Key Points:

🌟 Yuan3.0Flash is an open-source 40B-parameter multimodal foundation model that includes various model weights and detailed technical reports.  

💡 The model uses an innovative sparse mixture-of-experts architecture, significantly reducing computing power consumption during inference and enhancing intelligent performance.  

🚀 In enterprise applications, Yuan3.0Flash has surpassed GPT-5.1, demonstrating excellent multimodal reasoning capabilities and reducing application costs.