What are the hardware requirements for Codegemma 7B?

Codegemma 7B requires approximately 17 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Codegemma 7B and how large is it?

Codegemma 7B is developed by unsloth, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Codegemma 7B?

Codegemma 7B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Codegemma 7B by unsloth — VRAM 17GB, 8K context

Name: Codegemma 7B
Author: unsloth

Codegemma 7B is an open-source language model by unsloth. Features: 7b LLM, VRAM: 17GB, Context: 8K, License: apache-2.0, LLM Explorer Score: 0.12.

Bnb En Endpoints compatible Gemma Region:us Safetensors Sharded Tensorflow Unsloth

Model Card on HF 🤗: https://huggingface.co/unsloth/codegemma-7b

Codegemma 7B Parameters and Internals

Model Type

text generation

Use Cases

Areas:

beginner-friendly fine-tuning and text generation

Applications:

finetuning models for faster and memory-efficient performance, exporting models to various formats, uploading models to Hugging Face

Primary Use Cases:

2x faster fine-tuning

Additional Notes

Unsloth provides free Colab notebooks for beginners to finetune models efficiently.

LLM Name	Codegemma 7B
Repository 🤗	https://huggingface.co/unsloth/codegemma-7b
Model Size	7b
Required VRAM	17 GB
Updated	2026-08-04
Maintainer	unsloth
Model Type	gemma
Model Files	5.8 GB: 1-of-3 5.9 GB: 2-of-3 5.3 GB: 3-of-3
Supported Languages	en
Model Architecture	GemmaForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.44.2
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	bfloat16

Rank the Codegemma 7B capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Quantized Models of the Codegemma 7B

Model	Likes	Downloads	VRAM
Codegemma 7B AWQ	0	8	7 GB
CodeGemma 7B AWQ	0	6	7 GB

Best Alternatives to Codegemma 7B

Best Alternatives	Context / RAM	Downloads	Likes
Kaggle Math Model Gemma V1	12K / 17.1 GB	5	0
Gemma 1.1 7B It	8K / 17.1 GB	19153	275
Gemma 1.1 7B It	8K / 17.1 GB	8	4
Gemma 7B It	8K / 17.1 GB	3944	10
Gemma 1.1 7B It	8K / 17 GB	22	2
...emma 7B It Legal Refugiados Es	8K / 34 GB	5	0
SeaLLM 7B V2.5	8K / 17.1 GB	8761	51
Zephyr 7B Gemma DPO Avg	8K / 17.1 GB	15	0
Zephyr 7B Gemma Rpo Avg	8K / 17.1 GB	7	0
... Codegemma 2 7B It Alpaca V1.3	8K / 17.1 GB	7	1

Note: green Score (e.g. "73.2") means that the model is better than unsloth/codegemma-7b.