What are the hardware requirements for EZO Humanities 9B Gemma 2 It?

EZO Humanities 9B Gemma 2 It requires approximately 18.6 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 EZO Humanities 9B Gemma 2 It and how large is it?

EZO Humanities 9B Gemma 2 It is developed by AXCXEPT, a model with 9b 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 EZO Humanities 9B Gemma 2 It?

EZO Humanities 9B Gemma 2 It is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

EZO Humanities 9B Gemma 2 It by AXCXEPT — VRAM 18.6GB, 8K context

Name: EZO Humanities 9B Gemma 2 It
Author: AXCXEPT

EZO Humanities 9B Gemma 2 It is an open-source language model by AXCXEPT. Features: 9b LLM, VRAM: 18.6GB, Context: 8K, License: gemma, LLM Explorer Score: 0.13.

Conversational Endpoints compatible Gemma2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/AXCXEPT/EZO-Humanities-9B-gemma-2-it

EZO Humanities 9B Gemma 2 It Parameters and Internals

Model Type

Conversational, Text Generation

Use Cases

Areas:

Research, Global inquiries

Applications:

Humanities-related tasks such as literature, philosophy, history, and cultural studies

Primary Use Cases:

Understanding and generating responses in Humanities fields

Limitations:

No commercial use or critical deployments intended

Considerations:

None specified

Additional Notes

The model focuses on Japanese language processing while still being capable of handling a wide range of global inquiries.

Supported Languages

Japanese (Strong foundation), English (Capable)

Training Details

Data Sources:

Japanese Wikipedia, FineWeb

Data Volume:

Not specified

Methodology:

Plain instruction tuning

Training Time:

32 hours

Hardware Used:

A100 × 4

Model Architecture:

Gemma architecture used for tuning

Input Output

Input Format:

Model expects inputs following conversational structures.

Accepted Modalities:

text

Output Format:

Generates text-based responses.

Performance Tips:

Not specified

LLM Name	EZO Humanities 9B Gemma 2 It
Repository 🤗	https://huggingface.co/AXCXEPT/EZO-Humanities-9B-gemma-2-it
Model Size	9b
Required VRAM	18.6 GB
Updated	2026-09-10
Maintainer	AXCXEPT
Model Type	gemma2
Model Files	4.9 GB: 1-of-4 5.0 GB: 2-of-4 5.0 GB: 3-of-4 3.7 GB: 4-of-4
Model Architecture	Gemma2ForCausalLM
License	gemma
Context Length	8192
Model Max Length	8192
Transformers Version	4.42.3
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	bfloat16

Rank the EZO Humanities 9B Gemma 2 It 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 EZO Humanities 9B Gemma 2 It

Best Alternatives	Context / RAM	Downloads	Likes
G2 GSHT 32K	32K / 20.4 GB	8	1
SystemGemma2 9B It	32K / 18.6 GB	5	2
Gemma 2 9B It	8K / 18.6 GB	80757	11
GWQ 9B Preview2	8K / 18.6 GB	11	10
Gemma 2 9B It	8K / 18.6 GB	6	0
Gemma 2 9B It SimPO	8K / 18.6 GB	473	173
Gemma 2 9B It	8K / 18.6 GB	323635	837
Gemma 2 9B It Blend Rebase	8K / 20.4 GB	5	0
Gemma 2 9B	8K / 37.1 GB	95888	717
Gemma 2 9B JEE Socratic Final	8K / 18.6 GB	1118	0

Note: green Score (e.g. "73.2") means that the model is better than AXCXEPT/EZO-Humanities-9B-gemma-2-it.