Instructions to use cyankiwi/MiMo-V2-Flash-AWQ-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use cyankiwi/MiMo-V2-Flash-AWQ-4bit with Transformers:

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

pipe = pipeline("text-generation", model="cyankiwi/MiMo-V2-Flash-AWQ-4bit", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("cyankiwi/MiMo-V2-Flash-AWQ-4bit", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use cyankiwi/MiMo-V2-Flash-AWQ-4bit with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "cyankiwi/MiMo-V2-Flash-AWQ-4bit"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "cyankiwi/MiMo-V2-Flash-AWQ-4bit",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/cyankiwi/MiMo-V2-Flash-AWQ-4bit

SGLang

How to use cyankiwi/MiMo-V2-Flash-AWQ-4bit 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 "cyankiwi/MiMo-V2-Flash-AWQ-4bit" \
    --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": "cyankiwi/MiMo-V2-Flash-AWQ-4bit",
		"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 "cyankiwi/MiMo-V2-Flash-AWQ-4bit" \
        --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": "cyankiwi/MiMo-V2-Flash-AWQ-4bit",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use cyankiwi/MiMo-V2-Flash-AWQ-4bit with Docker Model Runner:
```
docker model run hf.co/cyankiwi/MiMo-V2-Flash-AWQ-4bit
```

Responses are in reasoning_content,but not content

by lluu8 - opened Dec 22, 2025

Discussion

lluu8

Dec 22, 2025

POST /v1/chat/completions HTTP/1.1
Host: 127.0.0.1:30000
Connection: keep-alive
Content-Length: 101
sec-ch-ua-platform: "Windows"
authorization: 123
___internal-request-id: fc6879cc-4b77-4907-b545-878041fab344
sec-ch-ua: "Google Chrome";v="143", "Chromium";v="143", "Not A(Brand";v="24"
content-type: application/json
sec-ch-ua-mobile: ?0
Accept: /
Sec-Fetch-Site: none
Sec-Fetch-Mode: cors
Sec-Fetch-Dest: empty
Sec-Fetch-Storage-Access: active
Accept-Encoding: gzip, deflate, br, zstd
Accept-Language: zh-CN,zh;q=0.9,en;q=0.8

{
"model": "mimo-v2-flash",
"messages": [
{"role": "user", "content": "Hi" }
]

}
HTTP/1.1 200 OK
date: Mon, 22 Dec 2025 08:16:08 GMT
server: uvicorn
content-length: 479
content-type: application/json

{"id":"1fe2258f0002469b9e5e612cf1f1947a","object":"chat.completion","created":1766391369,"model":"mimo-v2-flash","choices":[{"index":0,"message":{"role":"assistant","content":null,"reasoning_content":"Hello! How can I assist you today?","tool_calls":null},"logprobs":null,"finish_reason":"stop","matched_stop":151645}],"usage":{"prompt_tokens":27,"total_tokens":37,"completion_tokens":10,"prompt_tokens_details":null,"reasoning_tokens":0},"metadata":{"weight_version":"default"}}

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