Instructions to use OsaurusAI/MiniMax-M2.7-JANG_K with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use OsaurusAI/MiniMax-M2.7-JANG_K with MLX:

# Make sure mlx-lm is installed
# pip install --upgrade mlx-lm

# Generate text with mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("OsaurusAI/MiniMax-M2.7-JANG_K")

prompt = "Write a story about Einstein"
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
    messages, add_generation_prompt=True
)

text = generate(model, tokenizer, prompt=prompt, verbose=True)

Notebooks
Google Colab
Kaggle
Local Apps Settings
LM Studio

How to use OsaurusAI/MiniMax-M2.7-JANG_K 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-M2.7-JANG_K"

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/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-M2.7-JANG_K"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use OsaurusAI/MiniMax-M2.7-JANG_K 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-M2.7-JANG_K"

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-M2.7-JANG_K

Run Hermes

hermes

MLX LM

How to use OsaurusAI/MiniMax-M2.7-JANG_K with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Interactive chat REPL
mlx_lm.chat --model "OsaurusAI/MiniMax-M2.7-JANG_K"

Run an OpenAI-compatible server

# Install MLX LM
uv tool install mlx-lm
# Start the server
mlx_lm.server --model "OsaurusAI/MiniMax-M2.7-JANG_K"
# Calling the OpenAI-compatible server with curl
curl -X POST "http://localhost:8000/v1/chat/completions" \
   -H "Content-Type: application/json" \
   --data '{
     "model": "OsaurusAI/MiniMax-M2.7-JANG_K",
     "messages": [
       {"role": "user", "content": "Hello"}
     ]
   }'

MiniMax-M2.7-JANG_K / jang_config.json

Osaurus-AI

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	{
	"format": "jang",
	"format_version": "2.0",
	"quantization": {
	"method": "jang-affine-mixed",
	"profile": "JANG_K",
	"block_size": 128,
	"mode": "affine",
	"bit_widths_used": [
	2,
	4,
	6,
	8
	],
	"routed_avg_bits": 2.667,
	"awq": {
	"enabled": true,
	"alpha": 0.5,
	"scope": "routed_experts.gate_proj+up_proj (joint per-layer)",
	"fold_target": "post_attention_layernorm.weight",
	"scale_floor": 1.0
	}
	},
	"source_model": {
	"name": "MiniMax-M2.7-FP8",
	"dtype": "fp8_e4m3",
	"parameters": "227.6B"
	},
	"architecture": {
	"type": "moe",
	"attention": "gqa",
	"has_vision": false,
	"has_ssm": false,
	"has_moe": true
	},
	"capabilities": {
	"reasoning_parser": "qwen3",
	"tool_parser": "minimax",
	"think_in_template": true,
	"supports_tools": true,
	"supports_thinking": true,
	"family": "minimax_m2",
	"modality": "text",
	"cache_type": "kv"
	}
	}