Local AI is evolving REALLY fast Qwen 3.8 27B was released just 2 months ago and was smarter than O...
TL;DR · AI 摘要
本地AI模型在性能和效率上取得重大突破，MiniCPM-V 4.7以3B参数实现手机端运行并超越更大模型。
核心要点
- MiniCPM-V 4.7仅需3B参数即可在iPhone运行，性能超越10倍参数量的模型
- Qwen 3.8 27B虽性能更强但需要昂贵硬件支持
- OpenBMB推出的新模型将SOTA性能与移动端效率结合
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- 本地AI发展突破
- 模型对比
- Qwen 3.8 27B（高性能需昂贵硬件）
- MiniCPM-V 4.7（3B参数手机运行）
- 技术趋势
- 参数压缩技术突破
- 移动端算力优化
金句 / Highlights
值得收藏与分享的关键句。
MiniCPM-V 4.7在仅3B参数情况下，性能超越需要10倍参数量的模型
手机端运行的MiniCPM-V 4.7性能已超越6个月前最强大模型
OpenBMB新模型将SOTA性能与移动端效率结合，推动本地AI发展
Paul Couvert on X: "Local AI is evolving REALLY fast Qwen 3.8 27B was released just 2 months ago and was smarter than Opus 4.6 But you needed powerful/expensive hardware to run it MiniCPM-V 4.7 is as powerful and: - only 3B active parameters (!) - it runs even on an iphone - better than models… / X
Paul Couvert
@itsPaulAi
Local AI is evolving REALLY fast Qwen 3.8 27B was released just 2 months ago and was smarter than Opus 4.6 But you needed powerful/expensive hardware to run it MiniCPM-V 4.7 is as powerful and: - only 3B active parameters (!) - it runs even on an iphone - better than models w/ 10x more active parameters So you can run a model on a phone that is better than the most powerful one available 6 months ago. The future is local.
@OpenBMB
Oct 12
🚀 Introducing MiniCPM-V 4.7, our new open-source MLLM series! Advancing the Performance–Efficiency Pareto Frontier. It brings strong multimodal capabilities to iOS and Android devices with extreme efficiency. Two new models: 🔹 MiniCPM-V 4.7 35B-A3B — Bring SOTA performance to
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9:29 AM · Oct 13, 2026
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