What are the hardware requirements for Gemma 4 12B EsperGrug?

Gemma 4 12B EsperGrug requires approximately 23.8 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gemma 4 12B EsperGrug and how large is it?

Gemma 4 12B EsperGrug is developed by OliviaRossi, a model with 12b 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 12B EsperGrug?

Gemma 4 12B EsperGrug is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemma 4 12B EsperGrug by OliviaRossi — VRAM 23.8GB

Name: Gemma 4 12B EsperGrug
Author: OliviaRossi

Gemma 4 12B EsperGrug is an open-source language model by OliviaRossi. Features: 12b LLM, VRAM: 23.8GB, License: apache-2.0, LLM Explorer Score: 0.31.

Agentic Base model:kai-os/grug-12b Base model:merge:kai-os/grug-1... Base model:merge:valiantlabs/g... Base model:valiantlabs/gemma-4... Coding Conversational Devops En Gemma-4 Gemma4 unified Merge Mlops Reasoning Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/OliviaRossi/gemma-4-12B-EsperGrug

Gemma 4 12B EsperGrug Parameters and Internals

LLM Name	Gemma 4 12B EsperGrug
Repository 🤗	https://huggingface.co/OliviaRossi/gemma-4-12B-EsperGrug
Base Model(s)	Gemma 4 12B It Esper4 Grug 12B ValiantLabs/gemma-4-12B-it-Esper4 kai-os/Grug-12B
Model Size	12b
Required VRAM	23.8 GB
Updated	2026-10-08
Maintainer	OliviaRossi
Model Type	gemma4_unified
Model Files	0.0 GB: 1-of-14 2.0 GB: 2-of-14 1.9 GB: 3-of-14 1.9 GB: 4-of-14 2.0 GB: 5-of-14 1.9 GB: 6-of-14 1.9 GB: 7-of-14 1.9 GB: 8-of-14 2.0 GB: 9-of-14 2.0 GB: 10-of-14 1.9 GB: 11-of-14 2.0 GB: 12-of-14 1.9 GB: 13-of-14 0.5 GB: 14-of-14
Supported Languages	en
Model Architecture	Gemma4UnifiedForConditionalGeneration
License	apache-2.0
Transformers Version	5.13.1
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>

Rank the Gemma 4 12B EsperGrug 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

Best Alternatives to Gemma 4 12B EsperGrug

Best Alternatives	Context / RAM	Downloads	Likes
Gemma 4 12B It	0K / 23.9 GB	2965396	1417
Gemma 4 12B	0K / 23.9 GB	106193	768
...able5 Composer2.5 V2.3.5x Tau2	0K / 23.9 GB	242415	87
Jev Omni	0K / 23.9 GB	0	223
Gemma 4 12B It NVFP4	0K / 9.3 GB	47579	20
Gemma 4 12B It	0K / 23.9 GB	146843	15
...le5 Composer2.5 V1 Abliterated	0K / 24 GB	30003	1
Gemma 4 12B	0K / 23.9 GB	13026	18
...a 4 12B It W4a16 Llmcompressor	0K / 7.7 GB	2370	1
...It W4a16 Llmcompressor V0.12.0	0K / 7.7 GB	1880	1

Note: green Score (e.g. "73.2") means that the model is better than OliviaRossi/gemma-4-12B-EsperGrug.