ModelBest has introduced a new version of its lineup of multimodal models designed for device operation—MiniCPM-V 4.7. This model is available in two sizes: 35B-A3B and 1B. Notably, the 35B-A3B version is the first model in the MiniCPM-V series to feature a Mixture-of-Experts (MoE) architecture.
The weights, code, and documentation for this model have been published in the OpenBMB repository on GitHub under the Apache-2.0 license.
Efficiency on Mobile Devices
The primary claimed advantage is its high efficiency when running on smartphones. ModelBest asserts that the 35B-A3B model, which activates approximately 3 billion parameters per token, can operate on an iPhone 17 Pro Max using only about 3GB of RAM. Furthermore, its decoding speed exceeds 13 tokens per second.
The company attributes this result to a new inference acceleration technique they call LES (lookahead expert scheduling), characterizing the model as the first open-source MoE model capable of functioning seamlessly and without loss directly on the device.
Testing Results and Comparison
According to the team's presented benchmarks, the 35B-A3B model achieves the following results: 91.72 on MMBench, 91.2 on OCRBench, and 90.21 on CMMLU. In instruction mode, ModelBest claims it surpasses Qwen3.6 35B-A3B in overall score while requiring less reasoning time.
The 1B version has improved baseline capabilities compared to MiniCPM-V 4.6. Additionally, the company reports that this version outperforms Qwen3.5 0.8B in both overall score and inference efficiency.
Testing conducted by QbitAI showed that the model successfully handles graph reasoning tasks and converting academic articles into Markdown format, all while operating offline on a phone, which targets confidential local document processing.
Platform Support and Additional Tools
MiniCPM-V 4.7 supports iOS, Android, and HarmonyOS operating systems. The model has been adapted to work with chipset platforms from Intel, AMD, Arm, Rockchip, and Houmo AI, allowing it to be used on both mobile gadgets and local PCs.
Alongside the model itself, ModelBest has provided the open-source code for the Self-Replay Fine-Tuning (SRFT) method. This fine-tuning method is designed to assist developers in adding new features with minimal overhead while preventing the forgetting of previously acquired skills.
This release continues the steady rollout of models in the MiniCPM line, following MiniCPM-V 4.6 in May and the text model MiniCPM5-2B in September.