What are the hardware requirements for Gemopus 4 26B A4B It GGUF?

Gemopus 4 26B A4B It GGUF requires approximately 1.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gemopus 4 26B A4B It GGUF and how large is it?

Gemopus 4 26B A4B It GGUF is developed by Jackrong, a model with 26b 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 Gemopus 4 26B A4B It GGUF?

Gemopus 4 26B A4B It GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemopus 4 26B A4B It GGUF by Jackrong — VRAM 1.2GB

Name: Gemopus 4 26B A4B It GGUF
Author: Jackrong

Gemopus 4 26B A4B It GGUF is an open-source language model by Jackrong. Features: 26b LLM, VRAM: 1.2GB, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.29.

Alignment Conversational En Endpoints compatible Gemma Gemma4 Gguf Instruct Instruction-tuned Ja Ko Q4 Quantized Reasoning Region:us Zh

Model Card on HF 🤗: https://huggingface.co/Jackrong/Gemopus-4-26B-A4B-it-GGUF

Gemopus 4 26B A4B It GGUF Parameters and Internals

LLM Name	Gemopus 4 26B A4B It GGUF
Repository 🤗	https://huggingface.co/Jackrong/Gemopus-4-26B-A4B-it-GGUF
Model Name	unsloth/gemma-4-26B-A4B-it
Base Model(s)	google/gemma4-26B-it google/gemma4-26B-it
Model Size	26b
Required VRAM	1.2 GB
Updated	2026-06-30
Maintainer	Jackrong
Model Type	gemma4
Instruction-Based	Yes
Model Files	50.5 GB 16.8 GB 19.1 GB 18.0 GB 22.6 GB 26.9 GB 1.2 GB
Supported Languages	en zh ko ja
GGUF Quantization	Yes
Quantization Type	gguf\|q4\|q4_k\|q5_k
Model Architecture	Gemma4ForConditionalGeneration
License	apache-2.0
Torch Data Type	bfloat16

Rank the Gemopus 4 26B A4B It GGUF capabilities

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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

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