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

Gemma 2 (27B)

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

Repository editorial metadata; verify comparative claims in the linked upstream material.

24 GB catalogue minimum24 GB RAMQ5_K_MCoding assistant
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Parameters
27B
Minimum RAM
24 GB
Model size
16 GB
Quantization
Q5_K_M

Can Gemma 2 (27B) run locally?

Gemma 2 (27B) has a catalogue minimum of 24 GB RAM with Q5_K_M. Actual memory use and speed vary by context length, runtime, backend and system headroom.

Use gemma-2-27b-it as the catalogue search term in a compatible runtime, and confirm the available format on the upstream repository before download.

Public GGUF repository (verified 2026-09-07): lmstudio-community/gemma-2-27B-it-GGUFUpstream releasePaper or model cardLicence text
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.

Catalogue record

  • Family: gemma
  • Parameters: 27B
  • Recommended quantization: Q5_K_M
  • Catalogue minimum RAM: 24 GB
  • Catalogue model size: 16 GB
  • Tags: chat, code, power, quality

Practical limits

  • Catalogue RAM is a minimum estimate, not a guarantee for every context length or runtime.
  • Speed and memory use vary by quantization, backend, context length and system headroom.
  • Verify architecture, licence and usage restrictions in the linked upstream material before deployment.

Catalogue tags

  • chat
  • code
  • power
  • quality

Capability profile

Repository catalogue ratings used by LocalClaw's editorial rubric. They are not a standardized third-party benchmark.

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

Related catalogue entries

Linked mechanically by family, shared tags and nearby RAM tier; this is not a quality ranking.

Gemma 4 26B A4B 26B (A4B active)Gemma 3 (27B) 27BGemma 4 12B 12BGemma 4 31B 31BDiffusionGemma 26B-A4B Instruct 26B (4B active, diffusion MoE)Gemma 3 (12B) 12BGemma 2 (9B) 9BCodeGemma (7B) 7B

Where to go next