What are the hardware requirements for Gemma 4 26B A4B It Qat JANG 4M CRACK?

Gemma 4 26B A4B It Qat JANG 4M CRACK requires approximately 19 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gemma 4 26B A4B It Qat JANG 4M CRACK and how large is it?

Gemma 4 26B A4B It Qat JANG 4M CRACK is developed by dealignai, 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 Gemma 4 26B A4B It Qat JANG 4M CRACK?

Gemma 4 26B A4B It Qat JANG 4M CRACK is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemma 4 26B A4B It Qat JANG 4M CRACK by dealignai — VRAM 19GB

Name: Gemma 4 26B A4B It Qat JANG 4M CRACK
Author: dealignai

Gemma 4 26B A4B It Qat JANG 4M CRACK is an open-source language model by dealignai. Features: 26b LLM, VRAM: 19GB, License: gemma, LLM Explorer Score: 0.24.

Abliterated Conversational Crack Gemma4 Image-text-to-text Jang Mlx Moe Region:us Safetensors Sharded Tensorflow Uncensored

Model Card on HF 🤗: https://huggingface.co/dealignai/Gemma-4-26B-A4B-it-qat-JANG_4M-CRACK

Gemma 4 26B A4B It Qat JANG 4M CRACK Parameters and Internals

LLM Name	Gemma 4 26B A4B It Qat JANG 4M CRACK
Repository 🤗	https://huggingface.co/dealignai/Gemma-4-26B-A4B-it-qat-JANG_4M-CRACK
Base Model(s)	google/gemma-4-26b-a4b-it google/gemma-4-26b-a4b-it
Model Size	26b
Required VRAM	19 GB
Updated	2026-11-13
Maintainer	dealignai
Model Type	gemma4
Model Files	1.5 GB: 1-of-18 1.0 GB: 2-of-18 1.0 GB: 3-of-18 1.1 GB: 4-of-18 1.1 GB: 5-of-18 1.1 GB: 6-of-18 1.1 GB: 7-of-18 1.1 GB: 8-of-18 1.1 GB: 9-of-18 1.1 GB: 10-of-18 1.1 GB: 11-of-18 1.1 GB: 12-of-18 1.1 GB: 13-of-18 1.1 GB: 14-of-18 1.1 GB: 15-of-18 1.0 GB: 16-of-18 1.1 GB: 17-of-18 0.2 GB: 18-of-18
Model Architecture	Gemma4ForConditionalGeneration
License	gemma
Transformers Version	5.6.2
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>

Rank the Gemma 4 26B A4B It Qat JANG 4M CRACK 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

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GEV 26B Decide	0K / 51.6 GB	1013022	2316
Gemma 4 26B A4B It	0K / 51.6 GB	10405989	1007
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Gemma 4 26B A4B NVFP4	0K / 18.8 GB	1424962	126
Gemma 4 26B A4B It FP8 Dynamic	0K / 28.6 GB	1136349	38
Gemma 4 26B A4B It NVFP4	0K / 16.4 GB	742819	39

Note: green Score (e.g. "73.2") means that the model is better than dealignai/Gemma-4-26B-A4B-it-qat-JANG_4M-CRACK.