LocalClaw/LLM/CodeGemma (7B)
Open-weight local LLM

CodeGemma (7B)

Catalogue summary: Google code completion model. Excellent for inline code suggestions. 1.2M downloads.

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

8 GB catalogue minimum8 GB RAMQ5_K_MCoding assistant
Choose an app

Pick the app you already use. No terminal and no command to copy.

Compare models
Open in LM StudioOpens the app on this model's download screenOpen in UnslothLaunches Unsloth Desktop on this model's download page
OllamaNot available for this model
Open on Hugging FaceFiles, licence and available downloadsOpen llama.cpp setupAdvanced option: opens the model filesUse with LocalClawOptional workspace after the model is installed

Desktop app links require the app to be installed. If nothing opens, LocalClaw will show app-download and model-file fallbacks.

Parameters
7B
Minimum RAM
8 GB
Model size
4.5 GB
Quantization
Q5_K_M

Can CodeGemma (7B) run locally?

CodeGemma (7B) has a catalogue minimum of 8 GB RAM with Q5_K_M. Actual memory use and speed vary by context length, runtime, backend and system headroom.

Use codegemma-7b-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/codegemma-7b-it-GGUF
codestandard

Install path

01
Check RAM fitMinimum 8 GB RAM. Start with the Q5_K_M quant.
02
Load the modelSearch codegemma-7b-it in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Catalogue record

  • Family: gemma
  • Parameters: 7B
  • Recommended quantization: Q5_K_M
  • Catalogue minimum RAM: 8 GB
  • Catalogue model size: 4.5 GB
  • Tags: code, standard

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

  • code
  • standard

Capability profile

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

speed
8
quality
6
coding
8
reasoning
5

Technical notes

Developer
See upstream repository
License
See upstream repository
Context window
See upstream repository
Architecture
See upstream repository

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

Related catalogue entries

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

Gemma 2 (9B) 9BGemma 3 (4B) 4BGemma 4 E4B E4BGemma 4 12B 12BGemma 2 (27B) 27BGemma 4 26B A4B 26B (A4B active)Gemma 4 31B 31BGemma 3n (4B) 4B

Where to go next