LocalClaw/LLM/Gemma 4 E4B
Open-weight local LLM

Gemma 4 E4B

Gemma 4 balanced edge model with strong multimodal quality and 256K context. Great for laptops and high-end mobile devices. Apache 2.0.

Laptop ready 8 GB RAM Q4_K_M General assistant
Run with LocalClaw Compare all models
Parameters
E4B
Minimum RAM
8 GB
Model size
4.6 GB
Quantization
Q4_K_M

Can Gemma 4 E4B run locally?

Gemma 4 E4B is a good fit for normal laptops and compact desktops with 8 GB RAM or more.

Search for gemma-4-e4b-it in LM Studio or another GGUF-compatible runtime.

google/gemma-4-E4B-it
chatvisionstandardmultimodalreasoninggeneral

Install path

01
Check RAM fitMinimum 8 GB RAM. Start with the Q4_K_M quant.
02
Load the modelSearch gemma-4-e4b-it in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • Strong quality/speed balance
  • 256K context
  • Multimodal I/O support
  • Good fit for laptops and compact workstations

Limitations

  • Still below 26B/31B for advanced coding and deep reasoning

Best use cases

  • General assistant
  • Visual and audio understanding
  • Long-context summaries
  • Productivity copilots

Capability profile

speed
8
quality
7
coding
6
reasoning
7

Technical notes

Developer
Google DeepMind
License
Apache 2.0
Context window
262,144 tokens
Architecture
Gemma 4 multimodal Transformer (balanced edge tier)

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 4 12B 12BGemma 4 E2B E2BGemma 3n (8B) 8BQwen 3.5 (4B) 4B

Where to go next