What are the hardware requirements for Gemma 7B Malayalam T2 Gguf?

Gemma 7B Malayalam T2 Gguf requires approximately 5.3 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Gemma 7B Malayalam T2 Gguf and how large is it?

Gemma 7B Malayalam T2 Gguf is developed by animaRegem, 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 7B Malayalam T2 Gguf?

Gemma 7B Malayalam T2 Gguf is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Gemma 7B Malayalam T2 Gguf by animaRegem — VRAM 5.3GB

Name: Gemma 7B Malayalam T2 Gguf
Author: animaRegem

Gemma 7B Malayalam T2 Gguf is an open-source language model by animaRegem. Features: 7b LLM, VRAM: 5.3GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.12.

4bit Base model:quantized:unsloth/g... Base model:unsloth/gemma-7b-bn... En Endpoints compatible Gemma Gguf Quantized Region:us Unsloth

Model Card on HF 🤗: https://huggingface.co/animaRegem/gemma-7b-malayalam-t2-gguf

Gemma 7B Malayalam T2 Gguf Parameters and Internals

Model Type

text-generation-inference, transformers, unsloth, gemma, gguf

Additional Notes

This gemma model was trained 2x faster with Unsloth and Huggingface's TRL library.

Training Details

Training Time:

2x faster

LLM Name	Gemma 7B Malayalam T2 Gguf
Repository 🤗	https://huggingface.co/animaRegem/gemma-7b-malayalam-t2-gguf
Base Model(s)	Gemma 7B Bnb 4bit unsloth/gemma-7b-bnb-4bit
Model Size	7b
Required VRAM	5.3 GB
Updated	2026-07-21
Maintainer	animaRegem
Model Type	gemma
Model Files	5.3 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf\|4bit
Model Architecture	AutoModel
License	apache-2.0

Rank the Gemma 7B Malayalam T2 Gguf 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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Note: green Score (e.g. "73.2") means that the model is better than animaRegem/gemma-7b-malayalam-t2-gguf.