Instructions to use Intel/MiniMax-M3-MXFP4-CT-AutoRound with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Intel/MiniMax-M3-MXFP4-CT-AutoRound with Transformers:

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

pipe = pipeline("image-text-to-text", model="Intel/MiniMax-M3-MXFP4-CT-AutoRound", trust_remote_code=True)
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("Intel/MiniMax-M3-MXFP4-CT-AutoRound", trust_remote_code=True)
model = AutoModelForMultimodalLM.from_pretrained("Intel/MiniMax-M3-MXFP4-CT-AutoRound", trust_remote_code=True, device_map="auto")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Intel/MiniMax-M3-MXFP4-CT-AutoRound with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Intel/MiniMax-M3-MXFP4-CT-AutoRound"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Intel/MiniMax-M3-MXFP4-CT-AutoRound",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/Intel/MiniMax-M3-MXFP4-CT-AutoRound

SGLang

How to use Intel/MiniMax-M3-MXFP4-CT-AutoRound 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 "Intel/MiniMax-M3-MXFP4-CT-AutoRound" \
    --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": "Intel/MiniMax-M3-MXFP4-CT-AutoRound",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

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 "Intel/MiniMax-M3-MXFP4-CT-AutoRound" \
        --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": "Intel/MiniMax-M3-MXFP4-CT-AutoRound",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use Intel/MiniMax-M3-MXFP4-CT-AutoRound with Docker Model Runner:
```
docker model run hf.co/Intel/MiniMax-M3-MXFP4-CT-AutoRound
```

lvkaokao commited on Jul 20

Commit

69111de

verified ·

1 Parent(s): 2844e18

Update README.md

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@@ -16,11 +16,14 @@ This model is a MXFP4 mixed model of [MiniMax-M3](https://huggingface.co/MiniMax
 - MOE (block_sparse_moe.experts): MXFP4
 - MOE (block_sparse_moe.shared_experts): MXFP8
-| Configuration | GPQA_Diamond | AIME26 | SWE-Bench-Mini |
-|--------------|-------|----------|----------|----------|
-| BF16 | 0.9242 | 0.9 | 0.7|
 | MXFP8 | 0.9242 | 0.9333 | 0.68 |
-| MXFP4 (experts) + MXFP8 (shared_experts) | **0.9444** | **0.9667** | **0.74** |
 - The MXFP8 baseline model is from [MiniMaxAI/MiniMax-M3-MXFP8)](https://huggingface.co/MiniMaxAI/MiniMax-M3-MXFP8)

 - MOE (block_sparse_moe.experts): MXFP4
 - MOE (block_sparse_moe.shared_experts): MXFP8
+| Configuration | GPQA Diamond | AIME 2026 | SWE-Bench Mini |
+|---------------|--------------|-----------|----------------|
+| BF16 | 0.9242 | 0.9000 | 0.70 |
 | MXFP8 | 0.9242 | 0.9333 | 0.68 |
+| MXFP4 (Experts) + MXFP8 (Shared Experts) | **0.9444** | **0.9667** | **0.74** |
 - The MXFP8 baseline model is from [MiniMaxAI/MiniMax-M3-MXFP8)](https://huggingface.co/MiniMaxAI/MiniMax-M3-MXFP8)