LocalClaw/LLM/MiniMax M2.1
Open-weight MoE

MiniMax M2.1

MiniMax's open-source MoE model. Outstanding long-context capabilities up to 200K tokens. Ranks #8 on global usage leaderboards with 23.5B monthly tokens. Apache 2.0.

32 GB power user 24 GB RAM Q4_K_M Coding assistant
Run with LocalClaw Compare all models
Parameters
45B (MoE)
Minimum RAM
24 GB
Model size
18 GB
Quantization
Q4_K_M

Can MiniMax M2.1 run locally?

MiniMax M2.1 belongs on 32 GB machines when you want stronger quality without jumping to server hardware.

Search for minimax-m2.1 in LM Studio or another GGUF-compatible runtime.

MiniMaxAI/MiniMax-M2.1-GGUF
chatcodepowerqualitygeneral

Install path

01
Check RAM fitMinimum 24 GB RAM. Start with the Q4_K_M quant.
02
Load the modelSearch minimax-m2.1 in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • MiniMax's open-source MoE model. Outstanding long-context capabilities up to 200K tokens. Ranks #8 on global usage leaderboards with 23.5B monthly tokens. Apache 2.0.

Limitations

  • Performance depends on quantization, RAM bandwidth and runtime support.

Best use cases

  • chat
  • code
  • power
  • quality
  • general

Capability profile

speed
5
quality
9
coding
8
reasoning
9

Technical notes

Developer
minimax
License
See model repository
Context window
Unknown tokens
Architecture
See model card

This model fits these next steps

Hardware fit is based on LocalClaw's RAM tier, model size and quantization metadata. Always leave memory headroom for your OS and runtime.

Comfortable headroomMac mini M4 Pro 48GBMobile workstationMacBook Pro M4 Max 36GBPower-user picks32GB RAM guide

Where to go next