MiniMax-M2.5#

  • Context Length: 196608

  • Model Name: MiniMax-M2.5

  • Languages: en, zh

  • Abilities: chat, tools, reasoning

  • Description: MiniMax-M2.5, a Mini model built for Max coding & agentic workflows.

Specifications#

Model Spec 1 (pytorch, 230 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 230

  • Quantizations: none

  • Engines: vLLM, Transformers

  • Model ID: MiniMaxAI/MiniMax-M2.5

  • 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-M2.5 --size-in-billions 230 --model-format pytorch --quantization ${quantization}

Model Spec 2 (ggufv2, 230 Billion)#

  • Model Format: ggufv2

  • Model Size (in billions): 230

  • Quantizations: UD-TQ1_0

  • Engines: vLLM, llama.cpp

  • Model ID: unsloth/MiniMax-M2.5-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-M2.5 --size-in-billions 230 --model-format ggufv2 --quantization ${quantization}

Model Spec 3 (mlx, 230 Billion)#

  • Model Format: mlx

  • Model Size (in billions): 230

  • Quantizations: 3bit, 4bit, 5bit, 6bit, 8bit

  • Engines: MLX

  • Model ID: mlx-community/MiniMax-M2.5-{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-M2.5 --size-in-billions 230 --model-format mlx --quantization ${quantization}