Minimax M3 open weights release planned for Friday
Summary
MiniMaxAI announces plans to release open weights for its upcoming M3 model on Friday, following the earlier M2.7 model.
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Cached at: 06/11/26, 01:58 PM
MiniMaxAI/MiniMax-M2.7 · minimax 3 什么时候开源?
Source: https://huggingface.co/MiniMaxAI/MiniMax-M2.7/discussions/33 LibrariesTransformersHow to use MiniMaxAI/MiniMax-M2.7 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="MiniMaxAI/MiniMax-M2.7", trust_remote_code=True)
messages = [
{"role": "user", "content": "Who are you?"},
]
pipe(messages)
# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM
tokenizer = AutoTokenizer.from_pretrained("MiniMaxAI/MiniMax-M2.7", trust_remote_code=True)
model = AutoModelForMultimodalLM.from_pretrained("MiniMaxAI/MiniMax-M2.7", trust_remote_code=True)
messages = [
{"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.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=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
InferenceHuggingChatNotebooksGoogle ColabKaggleLocal AppsSettingsvLLMHow to use MiniMaxAI/MiniMax-M2.7 with vLLM:
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "MiniMaxAI/MiniMax-M2.7"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "MiniMaxAI/MiniMax-M2.7",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'
Use Docker
docker model run hf.co/MiniMaxAI/MiniMax-M2.7
SGLangHow to use MiniMaxAI/MiniMax-M2.7 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 "MiniMaxAI/MiniMax-M2.7" \
--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": "MiniMaxAI/MiniMax-M2.7",
"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 "MiniMaxAI/MiniMax-M2.7" \
--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": "MiniMaxAI/MiniMax-M2.7",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'
Docker Model RunnerHow to use MiniMaxAI/MiniMax-M2.7 with Docker Model Runner:
docker model run hf.co/MiniMaxAI/MiniMax-M2.7
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