Model card
MiniCPM-o-2_6 is an efficient 'any-to-any' multimodal model designed for real-time, seamless interaction across text, vision, and audio modalities. Unlike traditional pipelines that chain separate models for vision and speech, this model architecture enables direct cross-modal processing, significantly reducing latency for interactive applications. For developers, this means you can build sophisticated agents capable of seeing, hearing, and speaking within a single integrated framework. It is particularly optimized for edge deployment and mobile environments where computational resources are constrained, offering a high performance-to-parameter ratio. Whether you are working on real-time visual assistants, automated transcription with visual context, or complex multi-modal reasoning engines, MiniCPM-o-2_6 provides a versatile foundation that competes with much larger proprietary models while remaining accessible under the Apache-2.0 license.
Model files and versions
Download this model
We recommend using the ModelScope CLI or SDK. Install ModelScope first, then choose a full snapshot, single file, SDK or Git LFS workflow.
openbmb/MiniCPM-o-2_6Install the CLI and SDK dependency before downloading.
pip install modelscopeDownload the complete weights, configuration and model card.
modelscope download --model openbmb/MiniCPM-o-2_6README.md is used as an example; replace it with another repository file when needed.
modelscope download --model openbmb/MiniCPM-o-2_6 README.md --local_dir ./dirUseful in Python projects and automation scripts.
from modelscope import snapshot_download
model_dir = snapshot_download('openbmb/MiniCPM-o-2_6')Make sure Git LFS is installed correctly.
git lfs install
git clone https://www.modelscope.cn/openbmb/MiniCPM-o-2_6.gitFetch the repository structure first, then pull large files when needed.
GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/openbmb/MiniCPM-o-2_6.gitHow to use
- 01Step 1
Read the model card and source information.
- 02Step 2
Start with a small, non-sensitive evaluation.
- 03Step 3
Review quality, licensing and usage limits.
- 04Step 4
Adopt it only after validation.
Discussions
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