LocalClaw/LLM/Magistral (24B)
Open-weight local LLM

Magistral (24B)

Mistral efficient reasoning model. Strong chain-of-thought at 24B. 477K downloads.

32 GB power user 20 GB RAM Q4_K_M Complex reasoning
Run with LocalClaw Compare all models
Parameters
24B
Minimum RAM
20 GB
Model size
14 GB
Quantization
Q4_K_M

Can Magistral (24B) run locally?

Magistral (24B) belongs on 32 GB machines when you want stronger quality without jumping to server hardware.

Search for magistral-24b in LM Studio or another GGUF-compatible runtime.

mistralai/Magistral-24B-GGUF
reasoningpower

Install path

01
Check RAM fitMinimum 20 GB RAM. Start with the Q4_K_M quant.
02
Load the modelSearch magistral-24b in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • Efficient reasoning model
  • Apache 2.0
  • Strong chain-of-thought
  • 477K downloads

Limitations

  • Needs 20GB+ RAM
  • Reasoning overhead
  • New — less community support

Best use cases

  • Complex reasoning
  • Math
  • Strategic planning
  • Analysis

Capability profile

speed
5
quality
8
coding
7
reasoning
9

Technical notes

Developer
Mistral AI
License
Apache 2.0
Context window
131,072 tokens
Architecture
Transformer with reasoning-enhanced training

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

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Where to go next