LocalClaw/LLM/Mistral Small 3.1 (24B)
Open-weight local LLM

Mistral Small 3.1 (24B)

Mistral Small + vision + 128K context. See and understand images. 311K downloads.

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

Can Mistral Small 3.1 (24B) run locally?

Mistral Small 3.1 (24B) belongs on 32 GB machines when you want stronger quality without jumping to server hardware.

Search for mistral-small-3.1-24b-instruct in LM Studio or another GGUF-compatible runtime.

lmstudio-community/Mistral-Small-3.1-24B-Instruct-GGUF
chatvisionpower

Install path

01
Check RAM fitMinimum 20 GB RAM. Start with the Q4_K_M quant.
02
Load the modelSearch mistral-small-3.1-24b-instruct in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • Mistral Small + vision + 128K context. See and understand images. 311K downloads.

Limitations

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

Best use cases

  • chat
  • vision
  • power

Capability profile

speed
5
quality
8
coding
7
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