Instructions to use Ex0bit/MiniMax-M2.1-PRISM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Ex0bit/MiniMax-M2.1-PRISM with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Ex0bit/MiniMax-M2.1-PRISM", filename="MiniMax-M2.1-PRISM-IQ2_M.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use Ex0bit/MiniMax-M2.1-PRISM with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Ex0bit/MiniMax-M2.1-PRISM:IQ2_M # Run inference directly in the terminal: llama-cli -hf Ex0bit/MiniMax-M2.1-PRISM:IQ2_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Ex0bit/MiniMax-M2.1-PRISM:IQ2_M # Run inference directly in the terminal: llama-cli -hf Ex0bit/MiniMax-M2.1-PRISM:IQ2_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf Ex0bit/MiniMax-M2.1-PRISM:IQ2_M # Run inference directly in the terminal: ./llama-cli -hf Ex0bit/MiniMax-M2.1-PRISM:IQ2_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf Ex0bit/MiniMax-M2.1-PRISM:IQ2_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Ex0bit/MiniMax-M2.1-PRISM:IQ2_M
Use Docker
docker model run hf.co/Ex0bit/MiniMax-M2.1-PRISM:IQ2_M
- LM Studio
- Jan
- vLLM
How to use Ex0bit/MiniMax-M2.1-PRISM with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Ex0bit/MiniMax-M2.1-PRISM" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Ex0bit/MiniMax-M2.1-PRISM", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Ex0bit/MiniMax-M2.1-PRISM:IQ2_M
- Ollama
How to use Ex0bit/MiniMax-M2.1-PRISM with Ollama:
ollama run hf.co/Ex0bit/MiniMax-M2.1-PRISM:IQ2_M
- Unsloth Studio new
How to use Ex0bit/MiniMax-M2.1-PRISM with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Ex0bit/MiniMax-M2.1-PRISM to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Ex0bit/MiniMax-M2.1-PRISM to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Ex0bit/MiniMax-M2.1-PRISM to start chatting
- Pi new
How to use Ex0bit/MiniMax-M2.1-PRISM with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf Ex0bit/MiniMax-M2.1-PRISM:IQ2_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "Ex0bit/MiniMax-M2.1-PRISM:IQ2_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Ex0bit/MiniMax-M2.1-PRISM with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf Ex0bit/MiniMax-M2.1-PRISM:IQ2_M
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 Ex0bit/MiniMax-M2.1-PRISM:IQ2_M
Run Hermes
hermes
- Docker Model Runner
How to use Ex0bit/MiniMax-M2.1-PRISM with Docker Model Runner:
docker model run hf.co/Ex0bit/MiniMax-M2.1-PRISM:IQ2_M
- Lemonade
How to use Ex0bit/MiniMax-M2.1-PRISM with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Ex0bit/MiniMax-M2.1-PRISM:IQ2_M
Run and chat with the model
lemonade run user.MiniMax-M2.1-PRISM-IQ2_M
List all available models
lemonade list
Req: MLX Q4 or similar for 64GB Apple Silicon?
Hi, great work, excited to run this. I'd like to run it on 64GB Apple Silicon with less of a squeeze.
I hope it's ok to ask: would someone please be able to provide a MiniMax-M2.1-PRISM MLX 4bit (Q4_K_M style) build or similar, optimized for Apple Silicon (e.g., LM Studio)?
Thank you.
@JuanPabloski - We'll take a look at how to best provide additional quants while spreading the cost for custom asks. Please consider supporting our work.
Do you accept Bitcoin?
If you wish to sponsor our work Here's my BTC address:
bc1qkhh8k7t4v48g6sr0nxxjpevktkea8vmez97qas
-E.
If you wish to sponsor our work Here's my BTC address:
bc1qkhh8k7t4v48g6sr0nxxjpevktkea8vmez97qas-E.
I've sent something to your wallet, thank you very much for your work. I hope you can upload gguf or mlx quantizations of the glm 4.7 prism model.
Thank you @Asencion — much appreciated! We’re working on something very special. Stay tuned on X and HF for our next major releases.
For GLM-4.7, we’re developing a new class of REAPER-PRISM models: 2-bit and 4-bit lossless SigRoundV2 distill finetunes. Keep the support coming for upcoming drops!