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---
license: apache-2.0
language:
- zh
- en
pipeline_tag: text-generation
library_name: transformers
base_model: openbmb/MiniCPM4-MCP
tags:
- TensorBlock
- GGUF
---

<div style="width: auto; margin-left: auto; margin-right: auto">
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## openbmb/MiniCPM4-MCP - GGUF

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        Join our Discord to learn more about what we're building ↗
    </a>
</div>

This repo contains GGUF format model files for [openbmb/MiniCPM4-MCP](https://huggingface.co/openbmb/MiniCPM4-MCP).

The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b5753](https://github.com/ggml-org/llama.cpp/commit/73e53dc834c0a2336cd104473af6897197b96277).

## Our projects
<table border="1" cellspacing="0" cellpadding="10">
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    <th colspan="2">An OpenAI-compatible multi-provider routing layer.</th>
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    <th colspan="2">
      <a href="https://github.com/TensorBlock/forge" target="_blank" style="
        display: inline-block;
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      ">🚀 Try it now! 🚀</a>
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    <th style="font-size: 25px;">Awesome MCP Servers</th>
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    <th><img src="https://imgur.com/2Xov7B7.jpeg" alt="MCP Servers" width="450"/></th>
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    <th>A comprehensive collection of Model Context Protocol (MCP) servers.</th>
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      ">👀 See what we built 👀</a>
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        color: white;
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        border-radius: 6px;
        font-weight: bold;
        font-family: sans-serif;
      ">👀 See what we built 👀</a>
    </th>
  </tr>
</table>

## Prompt template

```
<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [MiniCPM4-MCP-Q2_K.gguf](https://huggingface.co/tensorblock/openbmb_MiniCPM4-MCP-GGUF/blob/main/MiniCPM4-MCP-Q2_K.gguf) | Q2_K | 3.117 GB | smallest, significant quality loss - not recommended for most purposes |
| [MiniCPM4-MCP-Q3_K_S.gguf](https://huggingface.co/tensorblock/openbmb_MiniCPM4-MCP-GGUF/blob/main/MiniCPM4-MCP-Q3_K_S.gguf) | Q3_K_S | 3.637 GB | very small, high quality loss |
| [MiniCPM4-MCP-Q3_K_M.gguf](https://huggingface.co/tensorblock/openbmb_MiniCPM4-MCP-GGUF/blob/main/MiniCPM4-MCP-Q3_K_M.gguf) | Q3_K_M | 4.015 GB | very small, high quality loss |
| [MiniCPM4-MCP-Q3_K_L.gguf](https://huggingface.co/tensorblock/openbmb_MiniCPM4-MCP-GGUF/blob/main/MiniCPM4-MCP-Q3_K_L.gguf) | Q3_K_L | 4.338 GB | small, substantial quality loss |
| [MiniCPM4-MCP-Q4_0.gguf](https://huggingface.co/tensorblock/openbmb_MiniCPM4-MCP-GGUF/blob/main/MiniCPM4-MCP-Q4_0.gguf) | Q4_0 | 4.684 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [MiniCPM4-MCP-Q4_K_S.gguf](https://huggingface.co/tensorblock/openbmb_MiniCPM4-MCP-GGUF/blob/main/MiniCPM4-MCP-Q4_K_S.gguf) | Q4_K_S | 4.718 GB | small, greater quality loss |
| [MiniCPM4-MCP-Q4_K_M.gguf](https://huggingface.co/tensorblock/openbmb_MiniCPM4-MCP-GGUF/blob/main/MiniCPM4-MCP-Q4_K_M.gguf) | Q4_K_M | 4.966 GB | medium, balanced quality - recommended |
| [MiniCPM4-MCP-Q5_0.gguf](https://huggingface.co/tensorblock/openbmb_MiniCPM4-MCP-GGUF/blob/main/MiniCPM4-MCP-Q5_0.gguf) | Q5_0 | 5.670 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [MiniCPM4-MCP-Q5_K_S.gguf](https://huggingface.co/tensorblock/openbmb_MiniCPM4-MCP-GGUF/blob/main/MiniCPM4-MCP-Q5_K_S.gguf) | Q5_K_S | 5.670 GB | large, low quality loss - recommended |
| [MiniCPM4-MCP-Q5_K_M.gguf](https://huggingface.co/tensorblock/openbmb_MiniCPM4-MCP-GGUF/blob/main/MiniCPM4-MCP-Q5_K_M.gguf) | Q5_K_M | 5.815 GB | large, very low quality loss - recommended |
| [MiniCPM4-MCP-Q6_K.gguf](https://huggingface.co/tensorblock/openbmb_MiniCPM4-MCP-GGUF/blob/main/MiniCPM4-MCP-Q6_K.gguf) | Q6_K | 6.717 GB | very large, extremely low quality loss |
| [MiniCPM4-MCP-Q8_0.gguf](https://huggingface.co/tensorblock/openbmb_MiniCPM4-MCP-GGUF/blob/main/MiniCPM4-MCP-Q8_0.gguf) | Q8_0 | 8.699 GB | very large, extremely low quality loss - not recommended |


## Downloading instruction

### Command line

Firstly, install Huggingface Client

```shell
pip install -U "huggingface_hub[cli]"
```

Then, downoad the individual model file the a local directory

```shell
huggingface-cli download tensorblock/openbmb_MiniCPM4-MCP-GGUF --include "MiniCPM4-MCP-Q2_K.gguf" --local-dir MY_LOCAL_DIR
```

If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:

```shell
huggingface-cli download tensorblock/openbmb_MiniCPM4-MCP-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```