What are the hardware requirements for Gemma 7B?

Gemma 7B requires approximately 17.1 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 Gemma 7B and how large is it?

Gemma 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 Gemma 7B?

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

Gemma 7B by unsloth — VRAM 17.1GB, 8K context

Name: Gemma 7B
Author: unsloth

Gemma 7B is an open-source language model by unsloth. Features: 7b LLM, VRAM: 17.1GB, Context: 8K, License: apache-2.0, LLM Explorer Score: 0.12.

En Endpoints compatible Gemma Gemma-7b Region:us Safetensors Sharded Tensorflow Unsloth

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

Gemma 7B Parameters and Internals

Model Type

Text Generation, Language Models

Use Cases

Areas:

Research, Commercial Applications

Applications:

Finetuning language models quickly and efficiently

Primary Use Cases:

Model finetuning with reduced memory and faster performance

Considerations:

The model finetuning process may have limitations based on the dataset and hardware used.

Additional Notes

The model supports quick and efficient finetuning through pre-developed notebooks accessible on platforms like Colab and Kaggle.

Input Output

Accepted Modalities:

Text

Performance Tips:

Ensure optimal hardware setup to maximize performance benefits.

LLM Name	Gemma 7B
Repository 🤗	https://huggingface.co/unsloth/gemma-7b
Model Size	7b
Required VRAM	17.1 GB
Updated	2026-07-20
Maintainer	unsloth
Model Type	gemma
Model Files	5.0 GB: 1-of-4 5.0 GB: 2-of-4 5.0 GB: 3-of-4 2.1 GB: 4-of-4
Supported Languages	en
Model Architecture	GemmaForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.52.4
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	bfloat16

Rank the Gemma 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

Best Alternatives to Gemma 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/gemma-7b.