MiniMax-M3#

  • Context Length: 1048576

  • Model Name: MiniMax-M3

  • Languages: en, zh

  • Abilities: chat, vision, tools, reasoning, hybrid

  • Description: MiniMax-M3 is a native multimodal model with 1M context. It has ~428B parameters and ~23B activated parameters.

Specifications#

Model Spec 1 (pytorch, 428 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 428

  • Quantizations: none

  • Engines: Transformers

  • Model ID: MiniMaxAI/MiniMax-M3

  • Model Hubs: Hugging Face, ModelScope

Execute the following command to launch the model, remember to replace ${quantization} with your chosen quantization method from the options listed above:

xinference launch --model-engine ${engine} --model-name MiniMax-M3 --size-in-billions 428 --model-format pytorch --quantization ${quantization}

Model Spec 2 (ggufv2, 428 Billion)#

  • Model Format: ggufv2

  • Model Size (in billions): 428

  • Quantizations: none

  • Engines: llama.cpp

  • Model ID: unsloth/MiniMax-M3-GGUF

  • Model Hubs: Hugging Face, ModelScope

Execute the following command to launch the model, remember to replace ${quantization} with your chosen quantization method from the options listed above:

xinference launch --model-engine ${engine} --model-name MiniMax-M3 --size-in-billions 428 --model-format ggufv2 --quantization ${quantization}

Model Spec 3 (mlx, 428 Billion)#

  • Model Format: mlx

  • Model Size (in billions): 428

  • Quantizations: 4bit

  • Engines: MLX

  • Model ID: mlx-community/MiniMax-M3-{quantization}

  • Model Hubs: Hugging Face, ModelScope

Execute the following command to launch the model, remember to replace ${quantization} with your chosen quantization method from the options listed above:

xinference launch --model-engine ${engine} --model-name MiniMax-M3 --size-in-billions 428 --model-format mlx --quantization ${quantization}