The fastest way to get this model running locally is via Docker.

Simply follow the directions outlined below.

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1-click setup: the app automatically fetches the large weight files.

Once launched, the setup wizard will detect your specs to configure the model for maximum efficiency.

🔍 Hash-sum: 33a20e718fb8bec383c433f99bdc7f86 | 🕓 Last update: 2026-06-25 Verify CPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: 32 GB highly recommended for 26B+ GGUF models Disk Space:70 GB free space for full FP16 weights storage Graphics: CUDA Compute Capability 8.0+ required for flash-attention

The MiniCPM-V-4.6 is a compact yet powerful vision-language model designed for real‑time multimodal understanding. It features a parameter count of 2.5B weights, enabling deployment on consumer‑grade hardware while maintaining high accuracy. The model accepts input images up to 1024×1024 resolution and processes them with a frame‑rate of 30 fps, making it suitable for live applications. In benchmark evaluations, MiniCPM-V-4.6 achieves state‑of‑the‑art performance on VQA and OCR tasks, often surpassing larger models by a significant margin. Its architecture incorporates a lightweight attention mechanism and efficient memory usage, allowing developers to integrate advanced visual AI without extensive computational resources.

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