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opengvlab 的网站图标

OpenGVLab: InternVL3 78B

opengvlab/internvl3-78b

模型权重

The InternVL3 series is an advanced multimodal large language model (MLLM). Compared to InternVL 2.5, InternVL3 demonstrates stronger multimodal perception and reasoning capabilities.

In addition, InternVL3 is benchmarked against the Qwen2.5 Chat models, whose pre-trained base models serve as the initialization for its language component. Benefiting from Native Multimodal Pre-Training, the InternVL3 series surpasses the Qwen2.5 series in overall text performance.

模态
发布时间
2025年9月15日
知识截止日期
2025年1月
活动常见问题探索

活动

此模型的 token 用量和请求流量随时间的变化。

目前无法通过 EU 区域内路由使用。 区域内路由文档

探索更多模型

具备视觉能力的 AI 模型:用于图像理解的多模态大语言模型集合AI 模型排行榜排名

常见问题

The InternVL3 series is an advanced multimodal large language model (MLLM). Compared to InternVL 2.5, InternVL3 demonstrates stronger multimodal perception and reasoning capabilities. In addition, InternVL3 is benchmarked against the Qwen2.5 Chat models, whose pre-trained base models serve as the initialization for its language component.

InternVL3 78B 接受 图像和文本 作为输入,并返回 文本。

InternVL3 78B 于 2025年9月15日 发布。其知识截止日期为 2025年1月31日。

更多模型,来自 opengvlab

InternVL3 14B

The 14b version of the InternVL3 series. An advanced multimodal large language model (MLLM) series that demonstrates superior overall performance. Compared to InternVL 2.5, InternVL3 exhibits superior multimodal perception and reasoning capabilities, while further extending its multimodal capabilities to encompass tool usage, GUI agents, industrial image analysis, 3D vision perception, and more.

文本32K 上下文
InternVL3 2B

The 2b version of the InternVL3 series, for an even higher inference speed and very reasonable performance. An advanced multimodal large language model (MLLM) series that demonstrates superior overall performance. Compared to InternVL 2.5, InternVL3 exhibits superior multimodal perception and reasoning capabilities, while further extending its multimodal capabilities to encompass tool usage, GUI agents, industrial image analysis, 3D vision perception, and more.

文本32K 上下文