LocalClaw/LLM/Gemma 4 12B
Open-weight local LLM

Gemma 4 12B

Google DeepMind 12B unified multimodal model. Text, image, audio and video inputs, 256K context, Apache 2.0, and a strong local sweet spot for 16-32 GB machines.

16 GB sweet spot 16 GB RAM Q4_K_M Private multimodal assistant
Run with LocalClaw Compare all models
Parameters
12B
Minimum RAM
16 GB
Model size
8.2 GB
Quantization
Q4_K_M

Can Gemma 4 12B run locally?

Gemma 4 12B is a practical pick for 16 GB machines, especially with Q4_K_M quantization.

Search for gemma-4-12b-it in LM Studio or another GGUF-compatible runtime.

Model sourcelmstudio-community/gemma-4-12B-it-GGUF
chatvisionaudiocodereasoningpowermultimodalgeneral

Install path

01
Check RAM fitMinimum 16 GB RAM. Start with the Q4_K_M quant.
02
Load the modelSearch gemma-4-12b-it in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • 12B local sweet spot
  • Unified text, image, audio and video input
  • 256K context window
  • Apache 2.0 license
  • Stronger ceiling than edge-size Gemma 4 variants

Limitations

  • Use the instruction-tuned variant for chat workflows
  • Very long context increases memory use
  • Runtime support may arrive at different speeds across LM Studio, Ollama, MLX and llama.cpp

Best use cases

  • Private multimodal assistant
  • Screenshot and document analysis
  • Local coding and reasoning
  • Long-context research on 32 GB machines

Capability profile

speed
6
quality
8
coding
8
reasoning
8

Technical notes

Developer
Google DeepMind
License
Apache 2.0
Context window
262,144 tokens
Architecture
Gemma 4 dense unified multimodal Transformer (12B)

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Where to go next