Install MiniCPM-V-4.6 Locally via Ollama 2 No Python Required

Install MiniCPM-V-4.6 Locally via Ollama 2 No Python Required

The fastest method for installing this model locally is by using Docker.

Follow the step-by-step instructions below.

Then, execute the docker-compose up command to launch the model.

🔒 Hash checksum: 1960abb0f008a5e3e0f033c3430e62a6 • 📆 Last updated: 2026-06-27



  • Processor: next-gen chip for heavy context processing
  • RAM: minimum 16 GB for stable 8B model loading
  • 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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