Deploy MiniCPM-V-4.6 Windows 10 Offline Setup

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

Simply follow the directions outlined below.

Next, run the Docker command to spin up the container.

🧩 Hash sum → 4ae1b4c42c253787d5c940cf7c746e49 — Update date: 2026-06-26

CPU: AVX2/AVX-512 instruction set required for llama.cpp
RAM: required: 16 GB absolute minimum for small models
Disk Space: free: 80 GB on system drive for scratch space
Graphics: 12 GB VRAM minimum required for basic quantization

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.

Parameters	2.5B
Image Input Size	1024×1024

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