Image-Text-to-Text
MLX
Safetensors
English
Chinese
minimax_m3_vl
jang
janght
quantized
apple-silicon
minimax
minimax_m3
Mixture of Experts
reasoning
thinking
agent
tool-use
vision
speculative-decoding
dspark
128gb
conversational
custom_code
Instructions to use OsaurusAI/MiniMax-M3.1-Flash-JANGHT1.9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use OsaurusAI/MiniMax-M3.1-Flash-JANGHT1.9 with MLX:
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("OsaurusAI/MiniMax-M3.1-Flash-JANGHT1.9") config = load_config("OsaurusAI/MiniMax-M3.1-Flash-JANGHT1.9") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Pi
How to use OsaurusAI/MiniMax-M3.1-Flash-JANGHT1.9 with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "OsaurusAI/MiniMax-M3.1-Flash-JANGHT1.9"
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "OsaurusAI/MiniMax-M3.1-Flash-JANGHT1.9" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent
How to use OsaurusAI/MiniMax-M3.1-Flash-JANGHT1.9 with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "OsaurusAI/MiniMax-M3.1-Flash-JANGHT1.9"
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default OsaurusAI/MiniMax-M3.1-Flash-JANGHT1.9
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use OsaurusAI/MiniMax-M3.1-Flash-JANGHT1.9 with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "OsaurusAI/MiniMax-M3.1-Flash-JANGHT1.9"
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "OsaurusAI/MiniMax-M3.1-Flash-JANGHT1.9" \ --custom-provider-id mlx-lm \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Download evaluation/reasoning_decision.json from OsaurusAI/MiniMax-M3.1-Flash-JANGHT1.9: direct link, hf CLI and curl.
- Browser
- Download file 3.2 kB
-
https://huggingface.co/OsaurusAI/MiniMax-M3.1-Flash-JANGHT1.9/resolve/main/evaluation/reasoning_decision.json
- Command line
-
hf download hf://OsaurusAI/MiniMax-M3.1-Flash-JANGHT1.9/evaluation/reasoning_decision.json
-
curl -L -o reasoning_decision.json https://huggingface.co/OsaurusAI/MiniMax-M3.1-Flash-JANGHT1.9/resolve/main/evaluation/reasoning_decision.json
3.2 kB
| { | |
| "what": "Adaptive reasoning decision gate: at every assistant-turn start in the held-out set (no prefix forced), the first token is the model's own choice between <mm:think> (think) and </mm:think> (answer directly). The bundle's choice vs the source's, teacher-forced.", | |
| "source": "MiniMaxAI/MiniMax-M3.1-Flash", | |
| "source_revision": "262ae6830934f3512211081b8a3f16425b93a239", | |
| "fields": { | |
| "n": "assistant-turn starts", | |
| "agree": "fraction where the bundle and the source make the same think / skip choice (argmax of the two tokens)", | |
| "ref_think": "fraction where the source thinks", | |
| "q_think": "fraction where the bundle thinks", | |
| "mean_abs_dp_think": "mean |P_bundle(<mm:think>) - P_source(<mm:think>)|" | |
| }, | |
| "by_effort_note": "effort = the reasoning_effort chat-template kwarg of the row; None = no effort tag", | |
| "all": { | |
| "n": 327, | |
| "agree": 0.9755351681957186, | |
| "ref_think": 0.8960244648318043, | |
| "q_think": 0.8899082568807339, | |
| "mean_abs_dp_think": 0.024736272980313813 | |
| }, | |
| "by_domain": { | |
| "agentic": { | |
| "n": 86, | |
| "agree": 0.9651162790697675, | |
| "ref_think": 0.627906976744186, | |
| "q_think": 0.6162790697674418, | |
| "mean_abs_dp_think": 0.06704882904586505 | |
| }, | |
| "coding": { | |
| "n": 49, | |
| "agree": 0.9183673469387755, | |
| "ref_think": 0.9591836734693877, | |
| "q_think": 0.9591836734693877, | |
| "mean_abs_dp_think": 0.021642896144900926 | |
| }, | |
| "long": { | |
| "n": 4, | |
| "agree": 1.0, | |
| "ref_think": 1.0, | |
| "q_think": 1.0, | |
| "mean_abs_dp_think": 3.337360472549511e-05 | |
| }, | |
| "multilingual": { | |
| "n": 40, | |
| "agree": 1.0, | |
| "ref_think": 1.0, | |
| "q_think": 1.0, | |
| "mean_abs_dp_think": 0.00015628930211283032 | |
| }, | |
| "reasoning": { | |
| "n": 45, | |
| "agree": 1.0, | |
| "ref_think": 1.0, | |
| "q_think": 1.0, | |
| "mean_abs_dp_think": 0.005851560307713704 | |
| }, | |
| "science": { | |
| "n": 33, | |
| "agree": 1.0, | |
| "ref_think": 1.0, | |
| "q_think": 1.0, | |
| "mean_abs_dp_think": 1.8494246537941788e-05 | |
| }, | |
| "story": { | |
| "n": 25, | |
| "agree": 1.0, | |
| "ref_think": 1.0, | |
| "q_think": 1.0, | |
| "mean_abs_dp_think": 0.0014211676723039268 | |
| }, | |
| "terminal": { | |
| "n": 45, | |
| "agree": 0.9777777777777777, | |
| "ref_think": 1.0, | |
| "q_think": 0.9777777777777777, | |
| "mean_abs_dp_think": 0.021249228293871006 | |
| } | |
| }, | |
| "by_effort": { | |
| "None": { | |
| "n": 194, | |
| "agree": 0.9742268041237113, | |
| "ref_think": 0.8917525773195877, | |
| "q_think": 0.8865979381443299, | |
| "mean_abs_dp_think": 0.024562513000013695 | |
| }, | |
| "high": { | |
| "n": 34, | |
| "agree": 0.9705882352941176, | |
| "ref_think": 0.8529411764705882, | |
| "q_think": 0.8235294117647058, | |
| "mean_abs_dp_think": 0.030750843035456197 | |
| }, | |
| "low": { | |
| "n": 24, | |
| "agree": 1.0, | |
| "ref_think": 1.0, | |
| "q_think": 1.0, | |
| "mean_abs_dp_think": 0.007379506022084735 | |
| }, | |
| "max": { | |
| "n": 38, | |
| "agree": 0.9736842105263158, | |
| "ref_think": 0.868421052631579, | |
| "q_think": 0.8421052631578947, | |
| "mean_abs_dp_think": 0.02558943064046118 | |
| }, | |
| "medium": { | |
| "n": 26, | |
| "agree": 0.9615384615384616, | |
| "ref_think": 0.8846153846153846, | |
| "q_think": 0.9230769230769231, | |
| "mean_abs_dp_think": 0.042194932052480864 | |
| }, | |
| "xhigh": { | |
| "n": 11, | |
| "agree": 1.0, | |
| "ref_think": 1.0, | |
| "q_think": 1.0, | |
| "mean_abs_dp_think": 0.0028663942838535613 | |
| } | |
| } | |
| } |