# Minicpm5 Deploy Llama Cpp

Run MiniCPM5-1B or MiniCPM5-2B with llama.cpp using the released GGUF artifacts (F16 /...

- Repository: https://github.com/OpenBMB/MiniCPM (11776 stars)
- Category: Engineering
- License: Apache-2.0
- Last updated: 2026-09-21
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add OpenBMB/MiniCPM --skill minicpm5-deploy-llama-cpp -g -a claude-code -y`
Codex: `npx skills add OpenBMB/MiniCPM --skill minicpm5-deploy-llama-cpp -g -a codex -y`
Cursor: `npx skills add OpenBMB/MiniCPM --skill minicpm5-deploy-llama-cpp -g -a cursor -y`
Gemini CLI: `npx skills add OpenBMB/MiniCPM --skill minicpm5-deploy-llama-cpp -g -a gemini-cli -y`

## Description

Run MiniCPM5-1B or MiniCPM5-2B with llama.cpp using the released GGUF artifacts (F16 / Q8_0 / Q4_K_M). Use when the user wants CPU-only / consumer-GPU / cross-platform native deployment, asks for "llama.cpp", "llama-cli", "llama-server", "GGUF", or has no Python available.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Deploy MiniCPM5-1B and MiniCPM5-2B with llama.cpp

CPU / edge / consumer-GPU deployment via the released GGUF artifacts. The artifacts work directly with vanilla `llama.cpp` and every downstream runtime (Ollama / LM Studio / `llama-cpp-python`).

## Required input

| Var | Example | Default |
| --- | --- | --- |
| `GGUF_REPO` | `openbmb/MiniCPM5-2B-GGUF` | required; `openbmb/MiniCPM5-1B-GGUF` also works |
| `QUANT` | `Q4_K_M` (1.56 GB, recommended) / `Q8_0` (2.68 GB) / `F16` (5.04 GB) | `Q4_K_M` |
| `NGL` | `99` (all layers on GPU) / `0` (CPU only) | `99` if NVIDIA GPU, else `0` |
| `CTX` | `8192` (default) up to `131072` (128 K) | `8192` |

## Steps

### 1. Install llama.cpp

```bash
# macOS
brew install llama.cpp

# Linux / cross-platform: pre-built binary
curl -fsSL https://github.com/ggerganov/llama.cpp/releases/latest/download/llama-cli-linux.tar.gz | tar -xz
# OR build from source:
git clone --depth=1 https://github.com/ggerganov/llama.cpp.git && cd llama.cpp
mkdir build && cd build
cmake .. -DGGML_CUDA=ON -DCMAKE_BUILD_TYPE=Release    # CPU-only: omit GGML_CUDA=ON
cmake --build . --config Release -j $(nproc) --target llama-cli llama-server
```

### 2. Download the GGUF

```bash
mkdir -p ~/minicpm5 && cd ~/minicpm5
huggingface-cli download ${GGUF_REPO} MiniCPM5-2B-${QUANT}.gguf --local-dir .
```

### 3a. Interactive chat (CLI)

```bash
llama-cli -m MiniCPM5-2B-${QUANT}.gguf \
    -n 2048 --temp 1.0 --top-p 0.95 --min-p 0.0 -ngl ${NGL} -c ${CTX}
```

### 3b. OpenAI-compatible HTTP server

```bash
llama-server -m MiniCPM5-2B-${QUANT}.gguf \
    --port 8080 -ngl ${NGL} -c ${CTX} --jinja
```

### 4. Validate

```bash
curl http://localhost:8080/v1/chat/completions \
    -H "Content-Type: application/json" \
    -d '{
        "model": "MiniCPM5-2B",
        "messages": [{"role":"user","content":"1+1=?"}],
        "temperature": 1.0, "top_p": 0.95, "min_p": 0.0, "max_tokens": 64
    }'
```

Expected: `"2"` in the reply.

The rest: https://github.com/OpenBMB/MiniCPM/blob/HEAD/skills/minicpm5-deploy-llama-cpp/SKILL.md