MiniCPM-V-4.6 Using Pinokio Full Speed NPU Mode Dummy Proof Guide

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

Refer to the instructions below to proceed.

The client handles the setup, pulling gigabytes of data automatically.

The smart installation system will instantly find the perfect configuration for your specific hardware.

🧾 Hash-sum — 1e0566ca7c51db62ab2a18879acfebc7 • 🗓 Updated on: 2026-06-28



  • Processor: 4.0 GHz+ boost clock recommended for CPU inference
  • RAM: required: 16 GB absolute minimum for small models
  • Disk Space: 80 GB NVMe SSD required for fast model weights loading
  • 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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