Deploying this model locally is quickest when done via Docker.

Refer to the instructions below to proceed.

The setup auto-streams the model assets (expect a multi-GB download).

During setup, the script automatically determines and applies the best settings tailored to your machine.

🧩 Hash sum → 0429ba35a61a560d12a9e722de07ebec — Update date: 2026-06-27 Verify Processor: next-gen chip for heavy context processing RAM: 32 GB or higher for smooth 32k context lengths Storage:100 GB free space for HuggingFace cache folder Graphics: TensorRT-LLM / vLLM inference engine compatible chip

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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