What are the hardware requirements for Gemma Ko 7B AWQ?

Gemma Ko 7B AWQ requires approximately 5.6 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 Ko 7B AWQ and how large is it?

Gemma Ko 7B AWQ is developed by ghost613, 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 Ko 7B AWQ?

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

Gemma Ko 7B AWQ by ghost613 — VRAM 5.6GB, 8K context

Name: Gemma Ko 7B AWQ
Author: ghost613

Gemma Ko 7B AWQ is an open-source language model by ghost613. Features: 7b LLM, VRAM: 5.6GB, Context: 8K, License: other, Quantized, LLM Explorer Score: 0.13.

4-bit Awq En Endpoints compatible Gemma Ko Pytorch Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/ghost613/gemma-ko-7b-AWQ

Gemma Ko 7B AWQ Parameters and Internals

Model Type

text-generation

Additional Notes

Quantized model from beomi/gemma-ko-7b. Original Gemma model page available.

Supported Languages

ko (proficient), en (proficient)

LLM Name	Gemma Ko 7B AWQ
Repository 🤗	https://huggingface.co/ghost613/gemma-ko-7b-AWQ
Model Size	7b
Required VRAM	5.6 GB
Updated	2026-05-26
Maintainer	ghost613
Model Type	gemma
Model Files	5.0 GB: 1-of-2 0.6 GB: 2-of-2
Supported Languages	ko en
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	GemmaForCausalLM
License	other
Context Length	8192
Model Max Length	8192
Transformers Version	4.41.1
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	float16

Rank the Gemma Ko 7B AWQ 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 Ko 7B AWQ

Best Alternatives	Context / RAM	Downloads	Likes
Gemma 1.1 7B It AWQ	8K / 7.2 GB	6	0
Codegemma 7B AWQ	8K / 7.2 GB	8	0
CodeGemma 7B AWQ	8K / 7.2 GB	6	0
SeaLLM 7B V2.5 AWQ	8K / 7.2 GB	5	2
SeaLLM 7B V2.5 AWQ	8K / 5.6 GB	7	0
Codegemma 1.1 7B It AWQ	8K / 7.2 GB	5	0
Gemma 7B It AWQ	8K / 7.2 GB	93	2
Gemma 7B It AWQ	8K / 7.2 GB	9	0
Gemma 7B AWQ	8K / 7.2 GB	6	0
...t Cleaner Gemma 32k Merged 16b	31K / 17.1 GB	7	0

Note: green Score (e.g. "73.2") means that the model is better than ghost613/gemma-ko-7b-AWQ.