MiniCPM-o

MiniCPM-o 2.6: An MLLM capable of delivering visual, voice, and multimodal interactions at GPT-4o level on mobile devices.

PremiumNewProductOthersMultimodalLanguage Model

Visit

MiniCPM-o 2.6 is the latest multimodal large language model (MLLM) developed by the OpenBMB team, featuring 8 billion parameters and capable of high-quality visual, voice, and multimodal interactions on edge devices like smartphones. This model is built on SigLip-400M, Whisper-medium-300M, ChatTTS-200M, and Qwen2.5-7B, trained in an end-to-end manner, and performs comparably to GPT-4o-202405. Its main advantages include leading visual capabilities, advanced voice functionality, powerful multimodal streaming abilities, impressive OCR performance, and superior efficiency. The model is open-source and free to use for academic research and commercial purposes.

Leading Visual Capability: Achieves an average score of 70.2 across 8 popular benchmarks like OpenCompass
surpassing many well-known models.
Advanced Voice Capability: Supports bilingual real-time voice conversations with configurable voices
excelling in voice comprehension tasks.
Robust Multimodal Streaming Ability: Can accept continuous video and audio streams
enabling real-time voice interactions.
Powerful OCR Performance: Processes images with any aspect ratio and resolutions up to 1.8 million pixels with exceptional OCR performance.
Superior Efficiency: Handles 1.8 million pixel images while generating only 640 tokens
enhancing inference speed and reducing memory usage.

\The target audience includes researchers
developers
and enterprises that need robust visual
voice
and multimodal interaction capabilities on mobile devices

In education
teachers can utilize MiniCPM-o 2.6 to create interactive teaching content
enhancing students' learning experiences through voice and visual aids.
Content creators can use this model to generate creative video scripts
integrating visual and audio elements to increase content appeal.

1. Clone the MiniCPM-o repository and navigate to the source folder.
2. Create and activate a conda environment.
3. Install the necessary dependencies.
4. Download and load the MiniCPM-o 2.6 model.
5. Use the PIL library to load images or other modal data.

Visit

MiniCPM-o Visit Over Time

Monthly Visits

490881889

Bounce Rate

37.92%

Page per Visit

5.6

Visit Duration

00:06:18

MiniCPM-o Visit Trend

MiniCPM-o Visit Geography

MiniCPM-o Traffic Sources

MiniCPM-o Alternatives

Qwen-VL — General-purpose Visual Language Model

Productivity•Visual•Language Model

2070

MiniCPM-o-2_6 — MiniCPM-o 2.6 is a powerful multimodal large language model designed for visual, speech, and multimodal live applications.

Others•Multimodal•Language Model

The Language of Motion — A unified model for verbal and non-verbal communication in 3D human motion.

Others•3D Human Motion•Multimodal

Spirit LM — Multimodal language model that integrates text and speech

Productivity•Multimodal•Language Model

108

ell — A lightweight programming library for language models, treating prompts as functions.

InternationalSelection•Language Model•Programming Library

156

VideoLLaMA2-7B — A large video-language model that provides video question answering and video captioning.

Video•Video Understanding•Language Model

534

Albus AI — A versatile AI workspace featuring a real-time voice assistant and a multimodal canvas, facilitating efficient creation and thought processing.

Productivity•Artificial Intelligence•Real-time Voice

Moondream AI — An open-source visual language model that operates on multiple devices.

Others•Artificial Intelligence•Open-source

InternVL2_5-38B-MPO — The InternVL2.5-MPO series models are based on InternVL2.5 and Hybrid Preference Optimization, showcasing exceptional performance.

chatting•Multimodal•Large Language Model

108

InternVL2_5-26B-MPO-AWQ — An advanced multimodal large language model with exceptional reasoning capabilities.

Programming•Multimodal•Large Language Model

Llama-3-Patronus-Lynx-70B-Instruct — An open-source evaluation model for detecting hallucinations, based on the Llama-3 architecture with 70 billion parameters.

Programming•Hallucination Detection•Language Model

CreatiLayout — CreatiLayout technology for creative layout-to-image generation is based on Siamese Multimodal Diffusion Transformers.

Image•Image Generation•Multimodal

216

CAG — An enhancement method for language models that improves generation efficiency through preloading knowledge caches without the need for real-time retrieval.

Programming•Natural Language Processing•Language Model

Eurus-2-7B-PRIME — A 7B parameter language model trained based on the PRIME methodology, specifically designed to enhance reasoning capabilities.

Programming•Reinforcement Learning•Reasoning Capability

Eurus-2-7B-SFT — Eurus-2-7B-SFT is a large language model optimized for mathematical capabilities, focusing on reasoning and problem-solving.

Programming•Artificial Intelligence•Language Model

VITA-1.5 — VITA-1.5: A GPT-4o level multimodal large language model for real-time visual and speech interaction.

Programming•Multimodal•Large Language Model

156

FlexRAG — A flexible and high-performance framework for information retrieval and generation

Programming•Information Retrieval•Generative Models

Sonus AI — Unlocker of future large language models

InternationalSelection•Artificial Intelligence•Language Model

InternVL2_5-26B-MPO — A multimodal large language model that enhances the interaction between visual and linguistic data.

Image•Multimodal•Large Language Model

102

InternVL2_5-8B-MPO-AWQ — A multimodal large language model enhancing visual and linguistic interaction capabilities.