# OpenBMB Releases MiniCPM-V for On-Device Vision

> The new open-source vision-language model is designed for high-resolution image understanding on mobile and edge devices.

Published by The Open Weights on Apr 13, 2026. Canonical: https://theopenweights.com/news/minicpm-v-4-6-ghgd

## Key facts

- Company: OpenBMB
- Model: MiniCPM-V 4.7 35B-A3B
- Version: 4.6
- Category: Vision-Language
- Modalities: Vision-Language
- License: Apache 2.0 (Open weights, commercial use allowed)
- Context window: 262K tokens
- Architecture: MiniCPMV4_6ForConditionalGeneration
- Precision: BF16
- Weights size: 2.6 GB
- Significance: notable
- Published: 2026-04-13
- Last verified: 2026-06-17
- Hugging Face: https://huggingface.co/openbmb/MiniCPM-V-4.6
- Canonical URL: https://theopenweights.com/news/minicpm-v-4-6-ghgd

AI research group OpenBMB has released MiniCPM-V-4.6, a lightweight, open-source vision-language model (VLM) explicitly designed for efficient performance on consumer hardware like mobile phones. The model aims to bring powerful multimodal understanding, previously limited to cloud-based services, directly to edge devices.

At its core, MiniCPM-V-4.6 combines the Llama-3-8B-Instruct language model with a SigLIP-400M vision encoder. According to the release details available on its [Hugging Face repository](https://huggingface.co/openbmb/MiniCPM-V-4.6), the model was trained on a 10 billion token dataset of high-quality image-text pairs. A key feature is its ability to process images at a high resolution of up to 1848x1848 pixels, which the developers claim gives it exceptional optical character recognition (OCR) capabilities.

## Performance and Features

OpenBMB reports that MiniCPM-V-4.6 demonstrates strong general-purpose visual understanding and instruction-following ability. Key highlights include:

*   **High-Resolution Support:** Enables detailed analysis and superior OCR.
*   **On-Device Focus:** Engineered for efficient inference on mobile and terminal devices.
*   **Open Access:** Released under the permissive Apache 2.0 license.

The developers claim the model surpasses several proprietary models, including GPT-4V, in certain open-ended evaluations, highlighting its strength in real-world visual reasoning tasks.

By targeting on-device deployment, MiniCPM-V-4.6 represents a significant step toward making advanced AI more accessible, private, and responsive. Running models locally reduces reliance on network connectivity and lowers latency, opening up new possibilities for real-time multimodal applications on personal devices.

## Get the model

- [Hugging Face](https://huggingface.co/openbmb/MiniCPM-V-4.6)

## Sources

- [openbmb/MiniCPM-V-4.6](https://huggingface.co/openbmb/MiniCPM-V-4.6) — Hugging Face, Apr 13, 2026

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Source: The Open Weights (https://theopenweights.com/). Aggregated and written by Claude, curated by humans. Cite as: "OpenBMB Releases MiniCPM-V for On-Device Vision", The Open Weights, Apr 13, 2026, https://theopenweights.com/news/minicpm-v-4-6-ghgd