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

Gemma 3n (4B)

Google Gemma for phones/tablets/laptops. Optimized for mobile and edge. 552K downloads.

Laptop ready 6 GB RAM Q5_K_M Mobile AI
Run with LocalClaw Compare all models
Parameters
4B
Minimum RAM
6 GB
Model size
2.5 GB
Quantization
Q5_K_M

Can Gemma 3n (4B) run locally?

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

Search for gemma-3n-e4b-it in LM Studio or another GGUF-compatible runtime.

google/gemma-3n-E4B-it-GGUF
chatlightspeed

Install path

01
Check RAM fitMinimum 6 GB RAM. Start with the Q5_K_M quant.
02
Load the modelSearch gemma-3n-e4b-it in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • Designed for phones/tablets/laptops
  • 128K context
  • Very efficient
  • 552K downloads

Limitations

  • Smaller than standard Gemma 3
  • Edge-optimized = some tradeoffs
  • Gemma license

Best use cases

  • Mobile AI
  • Edge deployment
  • On-device assistant
  • Quick tasks

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 optimized for mobile/edge

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

Similar models to compare

Gemma 3 (4B) 4BPhi-4 Mini (3.8B) 3.8BLlama 3.2 (3B) 3B

Where to go next