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微信视觉团队开源多模态嵌入模型WeMM-Embedding，提供2B/4B/9B版本
腾讯微信视觉团队宣布开源通用多模态嵌入模型WeMM-Embedding，支持文本和图像输入，推出2B、4B、9B三种规模，采用统一架构和两阶段训练、知识蒸馏技术。该模型已在微信推荐和搜索系统中部署，据称日调用量超十亿，但具体技术细节和验证数据未在摘要中提供。
AI推荐理由 腾讯微信视觉团队开源多模态嵌入模型WeMM-Embedding，提供2B/4B/9B三种规模，并宣称日调用量超十亿，但来源为AIbase转载，缺乏官方链接和详细技术验证，调用量数据未提供具体证据。对AI应用开发者有实际价值，但需谨慎对待宣传性数据。
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微信视觉团队开源通用多模态嵌入模型WeMM-Embedding，日调用量超百亿
AIbase基地
发布于AI新闻 · 2分钟阅读 · 2026年9月7日
16
近日，腾讯微信视觉团队正式宣布开源通用多模态嵌入模型WeMM-Embedding。该模型全面支持文本、图像等多模态输入，旨在通过先进的技术架构和训练策略，为AI应用开发者提供坚实的技术支持，进一步推动人工智能技术在更多垂直领域的创新应用。
在版本布局和技术架构方面，WeMM-Embedding推出了2B、4B和9B三种不同规模的版本，以满足多样化的部署需求。该模型采用统一架构设计，结合两阶段训练、知识蒸馏等核心技术，显著增强了多模态理解能力，同时在实际应用中有效平衡了部署效率。
作为经过真实业务场景严格检验的技术成熟成果，该模型现已广泛应用于微信的推荐和搜索系统，日在线调用量达到数十亿次。全面开源不仅标志着微信在构建多模态AI技术生态方面进一步开放，也将为行业内的AI应用开发提供强大的技术赋能。
腾讯微信多模态嵌入模型WeMM-Embedding AI应用开发
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WeChat Vision Team Opensources General Multimodal Embedding Model WeMM-Embedding, Daily Call Volume Exceeds Ten Billion
AIbase基地
Published inAI News · 2 min read · Sep 7, 2026
16
Recently, the WeChat Visual Team of Tencent officially announced the open-source of the general-purpose multimodal embedding model WeMM-Embedding. This model fully supports multimodal inputs such as text and images, aiming to provide solid technical support for AI application developers through advanced technical architecture and training strategies, further promoting the innovative applications of artificial intelligence technology in more vertical fields.
In terms of version layout and technical architecture, WeMM-Embedding has launched three versions with different scales: 2B, 4B, and 9B, to meet diverse deployment needs. The model adopts a unified architecture design combined with core technologies such as two-stage training and knowledge distillation, significantly enhancing multimodal understanding capabilities while effectively balancing deployment efficiency in practical applications.
As a technically matured result that has been rigorously tested in real business scenarios, the model is now widely deployed in WeChat's recommendation and search systems, with a daily online call volume reaching billions. The full open-source release not only marks further openness of WeChat in building a multimodal AI technology ecosystem but will also provide strong technical empowerment for AI application development in the industry.
TencentWeChatMultimodalEmbeddingModelWeMM-EmbeddingAIApplicationDevelopment
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