---

pipeline_tag: text-generation

base_model:

• openbmb/MiniCPM5-2B

license: apache-2.0

license_name: apache-2.0

library_name: llama-cpp

tags:

• minicpm5
• text-generation
• gguf
• quantized

languages:

• en
• zh

---

MiniCPM5-2B GGUF

GGUF quantized version of openbmb/MiniCPM5-2B, the second model in the MiniCPM5 series. It is a dense 2B Transformer (LlamaForCausalLM) built for on-device, local deployment, and resource-constrained scenarios, reaching 2B-class open-source SOTA.

Model Overview

MiniCPM5-2B is designed for local assistants, coding agents, tool-use workflows, and reasoning scenarios where a compact model is preferred. It keeps a small deployment footprint while providing native long-context support (131,072 tokens), and was post-trained with RL + OPD (On-Policy Distillation). It supports a chat template with thinking/reasoning mode (controlled via enable_thinking) and XML-style tool calling.

Model Architecture

| Property | Value |

| :--------------------------- | :--------------------------- |

| Architecture | LlamaForCausalLM (dense) |

| Total Parameters | 2.52B |

| Non-Embedding Parameters | 1.98B |

| Layers | 42 |

| Attention Heads (GQA) | 16 Q / 2 KV |

| Context Length | 131,072 (128K) |

| Original Precision | bfloat16 |

| Supported Languages | en, zh |

Available GGUF Files

| File | Quantization | Size | Use Case |

| :-------------------------- | :----------- | :---- | :---------------------------------------------- |

| minicpm5-2b-bf16.gguf | BF16 | 4.7 GB | Full precision (reference quality) |

| minicpm5-2b-Q8_0.gguf | Q8_0 | 2.5 GB | Near-lossless, low overhead |

| minicpm5-2b-Q6_K.gguf | Q6_K | 2.0 GB | Very high quality |

| minicpm5-2b-Q5_K_M.gguf | Q5_K_M | 1.7 GB | High quality, balanced |

| minicpm5-2b-Q5_K_S.gguf | Q5_K_S | 1.7 GB | High quality, slightly smaller |

| minicpm5-2b-Q4_K_M.gguf | Q4_K_M | 1.5 GB | Recommended: good quality/size trade-off |

| minicpm5-2b-Q4_K_S.gguf | Q4_K_S | 1.4 GB | Smaller, slight quality loss |

| minicpm5-2b-Q4_0.gguf | Q4_0 | 1.4 GB | Legacy 4-bit, broad compatibility |

DSpark Draft Model (Speculative Decoding)

| File | Quantization | Size | Use Case |

| :------------------------------- | :----------- | :---- | :---------------------------------------------- |

| minicpm5-2b-dspark-bf16.gguf | BF16 | 623 MB | Draft model, full precision |

| minicpm5-2b-dspark-Q8_0.gguf | Q8_0 | 334 MB | Draft model, near-lossless |

| minicpm5-2b-dspark-Q4_K_M.gguf | Q4_K_M | 186 MB | Draft model, smallest footprint |

These are the MiniCPM5-2B-DSpark draft models, trained for speculative decoding with MiniCPM5-2B. They accelerate generation without changing the target model's outputs.

Usage

llama.cpp CLI

./llama-cli \
  -m minicpm5-2b-Q4_K_M.gguf \
  -p "Explain quantum computing in simple terms." \
  --temp 1.0 --top-p 0.95

llama-server (OpenAI-compatible API)

./llama-server \
  -m minicpm5-2b-Q4_K_M.gguf \
  --host 0.0.0.0 --port 8080

The GGUF also works with Ollama and LM Studio.

Speculative Decoding (DSpark)

Pair the target model with a DSpark draft model to speed up inference. Draft model quality has minimal impact on output, so smaller quants (e.g. Q4_K_M) are usually fine:

./llama-server \
  -m minicpm5-2b-Q4_K_M.gguf \
  -md minicpm5-2b-dspark-Q4_K_M.gguf \
  --host 0.0.0.0 --port 8080

Thinking Mode

The model supports deep-thinking output. You can control it per request via the chat template, e.g. with an OpenAI-compatible API:

"chat_template_kwargs": {"enable_thinking": false}

Tool Calling

MiniCPM5-2B emits XML-style tool calls. Tool definitions are injected into the prompt, and tool results are returned in the observation/tool role. SGLang's built-in minicpm5 parser converts these to OpenAI-compatible tool_calls natively (see upstream model card).

Generation Parameters

Recommended parameters from the original model:

| Parameter | Value |

| :------------ | :---- |

| Temperature | 1.0 |

| Top-P | 0.95 |

Quantization

These GGUF files were created from the BF16 source model using llama-quantize from the llama.cpp project.

Acknowledgements

• Original model: openbmb/MiniCPM5-2B
• Draft model: openbmb/MiniCPM5-2B-DSpark
• Quantization tool: llama.cpp

License

Apache-2.0 License