LocalClaw/LLM/Mistral Small 3.2 (24B)
Open-weight local LLM

Mistral Small 3.2 (24B)

Mistral AI's latest dense 24B. Improved instruction following, function calling, and reduced repetition. Strong European-language support. 128K context. Apache 2.0.

32 GB power user 24 GB RAM Q5_K_M Coding assistant
Run with LocalClaw Compare all models
Parameters
24B
Minimum RAM
24 GB
Model size
14 GB
Quantization
Q5_K_M

Can Mistral Small 3.2 (24B) run locally?

Mistral Small 3.2 (24B) belongs on 32 GB machines when you want stronger quality without jumping to server hardware.

Search for mistral-small-3.2-24b-instruct in LM Studio or another GGUF-compatible runtime.

mistralai/Mistral-Small-3.2-24B-Instruct-2506-GGUF
chatcodepowergeneralreasoning

Install path

01
Check RAM fitMinimum 24 GB RAM. Start with the Q5_K_M quant.
02
Load the modelSearch mistral-small-3.2-24b-instruct in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • Mistral AI's latest dense 24B. Improved instruction following, function calling, and reduced repetition. Strong European-language support. 128K context. Apache 2.0.

Limitations

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

Best use cases

  • chat
  • code
  • power
  • general
  • reasoning

Capability profile

speed
6
quality
8
coding
8
reasoning
8

Technical notes

Developer
mistral
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