What are the hardware requirements for Unsloth Finetune VLM?

Unsloth Finetune VLM requires approximately 1.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Unsloth Finetune VLM and how large is it?

Unsloth Finetune VLM is developed by cheahour. 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 Unsloth Finetune VLM?

Unsloth Finetune VLM is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Unsloth Finetune VLM by cheahour — VRAM 1.4GB

Name: Unsloth Finetune VLM
Author: cheahour

Unsloth Finetune VLM is an open-source language model by cheahour. Features: LLM, VRAM: 1.4GB, License: apache-2.0, Quantized, Fine-Tuned, LLM Explorer Score: 0.28.

4bit Conversational En Endpoints compatible Finetuned Gemma4 Image-text-to-text Quantized Region:us Sharded Tensorflow Unsloth

Model Card on HF 🤗: https://huggingface.co/cheahour/unsloth_finetune_VLM

Unsloth Finetune VLM Parameters and Internals

LLM Name	Unsloth Finetune VLM
Repository 🤗	https://huggingface.co/cheahour/unsloth_finetune_VLM
Base Model(s)	unsloth/gemma-4-e2b-it-unsloth-bnb-4bit unsloth/gemma-4-e2b-it-unsloth-bnb-4bit
Required VRAM	1.4 GB
Updated	2026-09-16
Maintainer	cheahour
Model Type	gemma4
Model Files	1.4 GB: 1-of-5
Supported Languages	en
Quantization Type	4bit
Model Architecture	Gemma4ForConditionalGeneration
License	apache-2.0
Model Max Length	131072
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Torch Data Type	bfloat16

Rank the Unsloth Finetune VLM 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 Unsloth Finetune VLM

Best Alternatives	Context / RAM	Downloads	Likes
...s Reasoning GeminiCLI Mlx 4bit	0K / 11 GB	156680	31
Gemma 4 E4B It GGUF	0K / 1 GB	510433	566
OTel LLM E4B IT	0K / 31.5 GB	4677244	0
Gemma 4 E2B It GGUF	0K / 0.1 GB	496984	256
Sulphur Caption	0K / GB	47	4
Lemer	0K / 3.2 GB	292	2

Note: green Score (e.g. "73.2") means that the model is better than cheahour/unsloth_finetune_VLM.