MiniCPM 2.4.2

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type: entity tags: [model, on-device, openbmb, quantization, multimodal] related: [[gemma4-ondevice]], [[ggml-llamacpp-hf]], [[on-device-inference-memory-pressure]] sources: - https://github.com/OpenBMB/MiniCPM/releases/tag/2.4.2 created: 2026-04-14

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核心问题

The recent surge of Multimodal Large Language Models (MLLMs) has fundamentally reshaped the landscape of AI research and industry, shedding light on a promising path toward the next AI milestone. However, significant challenges remain preventing MLLMs from being practical in real-world applications. The most notable challenge comes from the huge cost of running an MLLM with a massive number of parameters and extensive computation. As a result, most MLLMs need to be deployed on high-performing cloud servers, which greatly limits their application scopes such as mobile, offline, energy-sensitive

论文信息

• 标题: MiniCPM-V: A GPT-4V Level MLLM on Your Phone
• 作者: Yuan Yao, Tianyu Yu, Ao Zhang
• 来源: arXiv

方法/架构

详细方法论待补充。参考原始论文获取完整技术细节。

为什么重要

作为手机端 AIOS 生态的一部分，MiniCPM 2.4.2 对推动端侧 AI 落地具有重要意义。

关联

• [[clawmobile-agentic]] — Agent 系统参考
• [[mnn-350]] — 推理引擎