LocalClaw/LLM/Gemma 2 (27B)
Open-weight local LLM

Gemma 2 (27B)

Google's large Gemma 2. Excellent reasoning and coding. Strong performance at 27B.

32 GB power user 24 GB RAM Q5_K_M Advanced reasoning
Run with LocalClaw Compare all models
Parameters
27B
Minimum RAM
24 GB
Model size
16 GB
Quantization
Q5_K_M

Can Gemma 2 (27B) run locally?

Gemma 2 (27B) belongs on 32 GB machines when you want stronger quality without jumping to server hardware.

Search for gemma-2-27b-it in LM Studio or another GGUF-compatible runtime.

lmstudio-community/gemma-2-27B-it-GGUF
chatcodepowerquality

Install path

01
Check RAM fitMinimum 24 GB RAM. Start with the Q5_K_M quant.
02
Load the modelSearch gemma-2-27b-it in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • Near-frontier quality at 27B
  • Strong reasoning and coding
  • Efficient architecture

Limitations

  • 8K context limit
  • Needs 24GB+ RAM
  • Gemma license restrictions

Best use cases

  • Advanced reasoning
  • Professional coding assistance
  • Research
  • Content creation

Capability profile

speed
4
quality
9
coding
8
reasoning
8

Technical notes

Developer
Google DeepMind
License
Gemma License
Context window
8,192 tokens
Architecture
Transformer (decoder-only) with sliding window attention

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

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Where to go next