Instructions to use openbmb/MiniCPM4.1-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use openbmb/MiniCPM4.1-8B with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="openbmb/MiniCPM4.1-8B", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("openbmb/MiniCPM4.1-8B", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use openbmb/MiniCPM4.1-8B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "openbmb/MiniCPM4.1-8B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "openbmb/MiniCPM4.1-8B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/openbmb/MiniCPM4.1-8B

SGLang

How to use openbmb/MiniCPM4.1-8B with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "openbmb/MiniCPM4.1-8B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "openbmb/MiniCPM4.1-8B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "openbmb/MiniCPM4.1-8B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "openbmb/MiniCPM4.1-8B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use openbmb/MiniCPM4.1-8B with Docker Model Runner:
```
docker model run hf.co/openbmb/MiniCPM4.1-8B
```

MiniCPM4.1-8B

Commit History

Sep 30, 2025

19:22
Improve model card: Add InfLLM-V2 paper details and comprehensive citations⁠

nielsr HF Staff

Verified signature
345e687
02:50
Merge branch 'main' of hf.co:openbmb/MiniCPM4.1-8B

xcjthu

6170bc9
02:48
update usage for sparse attention

xcjthu

8ab8cc2

Sep 16, 2025

05:52
Update README.md

beyoung

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Sep 12, 2025

14:30
update requirements for transformers version

xcjthu

ef9ecae

Sep 11, 2025

13:48
add \n

xcjthu

a5b27c8
13:46
add \n

xcjthu

7038d5f
13:37
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xcjthu

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Sep 5, 2025

14:51
update README.md

BigDong

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09:47
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09:28
update long rope setting

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4a06b69
09:21
update readme and modeling model

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f37d55b

Sep 2, 2025

08:00
first commit

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84eb0ec
07:14
initial commit

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Commit History

Sep 30, 2025

Improve model card: Add InfLLM-V2 paper details and comprehensive citations⁠

Merge branch 'main' of hf.co:openbmb/MiniCPM4.1-8B

update usage for sparse attention

Sep 16, 2025

Update README.md

Sep 12, 2025

update requirements for transformers version

Sep 11, 2025

add \n

add \n

update readme for better presentation

Sep 5, 2025

update README.md

update README.md

update README.md

update README.md

update README.md

update README.md

update README.md

minor update config.json

update paper link

minor update config.json

update long rope setting

update readme and modeling model

Sep 2, 2025

first commit

initial commit