minicpm5-1b#
Context Length: 131072
Model Name: minicpm5-1b
Languages: en, zh
Abilities: chat, reasoning, hybrid, tools
Description: MiniCPM5-1B is the first model in the MiniCPM5 series. It is a dense 1B Transformer built for on-device, local deployment, and resource-constrained scenarios, reaching 1B-class open-source SOTA. Supports hybrid thinking via enable_thinking and native XML-style tool calling (MCP-compatible).
Specifications#
Model Spec 1 (pytorch, 1 Billion)#
Model Format: pytorch
Model Size (in billions): 1
Quantizations: none
Engines: vLLM, Transformers, SGLang
Model ID: openbmb/MiniCPM5-1B
Model Hubs: Hugging Face, ModelScope
Execute the following command to launch the model, remember to replace ${quantization} with your
chosen quantization method from the options listed above:
xinference launch --model-engine ${engine} --model-name minicpm5-1b --size-in-billions 1 --model-format pytorch --quantization ${quantization}
Model Spec 2 (ggufv2, 1 Billion)#
Model Format: ggufv2
Model Size (in billions): 1
Quantizations: F16, Q4_K_M, Q8_0
Engines: vLLM, llama.cpp
Model ID: openbmb/MiniCPM5-1B-GGUF
Model Hubs: Hugging Face, ModelScope
Execute the following command to launch the model, remember to replace ${quantization} with your
chosen quantization method from the options listed above:
xinference launch --model-engine ${engine} --model-name minicpm5-1b --size-in-billions 1 --model-format ggufv2 --quantization ${quantization}
Model Spec 3 (mlx, 1 Billion)#
Model Format: mlx
Model Size (in billions): 1
Quantizations: 4bit
Engines: MLX
Model ID: openbmb/MiniCPM5-1B-MLX
Model Hubs: Hugging Face, ModelScope
Execute the following command to launch the model, remember to replace ${quantization} with your
chosen quantization method from the options listed above:
xinference launch --model-engine ${engine} --model-name minicpm5-1b --size-in-billions 1 --model-format mlx --quantization ${quantization}