LocalClaw/LLM/Gemma 3 (4B)
Open-weight local LLM

Gemma 3 (4B)

Google's multimodal gem. Understands text AND images natively. Great quality-to-size ratio.

Laptop ready 8 GB RAM Q5_K_M Long document processing
Run with LocalClaw Compare all models
Parameters
4B
Minimum RAM
8 GB
Model size
3 GB
Quantization
Q5_K_M

Can Gemma 3 (4B) run locally?

Gemma 3 (4B) is a good fit for normal laptops and compact desktops with 8 GB RAM or more.

Search for gemma-3-4b-it in LM Studio or another GGUF-compatible runtime.

lmstudio-community/gemma-3-4B-it-GGUF
chatvisionstandardgeneral

Install path

01
Check RAM fitMinimum 8 GB RAM. Start with the Q5_K_M quant.
02
Load the modelSearch gemma-3-4b-it in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • 128K context window at only 4B
  • Multimodal (image understanding)
  • Excellent for its size
  • 140+ languages

Limitations

  • Not as strong as 8B+ models on hard tasks
  • Vision capabilities basic compared to specialized models

Best use cases

  • Long document processing
  • Multilingual chat
  • Basic image analysis
  • Mobile/edge deployment

Capability profile

speed
9
quality
6
coding
5
reasoning
6

Technical notes

Developer
Google DeepMind
License
Gemma License
Context window
131,072 tokens
Architecture
Transformer with 128K context, vision support

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.

Entry laptop fitMacBook Air 8GBMore headroomMac mini M4 16GBAll compatible picks8GB RAM guide

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Where to go next