What are the hardware requirements for VQS?

VQS requires approximately 4.3 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed VQS and how large is it?

VQS is developed by ahmedheakl, a model with 2b 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 VQS?

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

VQS by ahmedheakl — VRAM 4.3GB

Name: VQS
Author: ahmedheakl

VQS is an open-source language model by ahmedheakl. Features: 2b LLM, VRAM: 4.3GB, Instruction-Based, LLM Explorer Score: 0.28.

Arxiv:2609.33855 Base model:finetune:qwen/qwen3... Base model:qwen/qwen3-vl-2b-in... Conversational Endpoints compatible Grpo Image-text-to-text Instruct Qwen3-vl Qwen3 vl Region:us Safetensors Self-evolution Self-training Vision Vision-language

Model Card on HF 🤗: https://huggingface.co/ahmedheakl/VQS

VQS Parameters and Internals

LLM Name	VQS
Repository 🤗	https://huggingface.co/ahmedheakl/VQS
Base Model(s)	Qwen3 VL 2B Instruct Qwen/Qwen3-VL-2B-Instruct
Model Size	2b
Required VRAM	4.3 GB
Updated	2026-10-01
Maintainer	ahmedheakl
Model Type	qwen3_vl
Instruction-Based	Yes
Model Files	4.3 GB
Model Architecture	Qwen3VLForConditionalGeneration
Model Max Length	262144
Transformers Version	4.57.6
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the VQS 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 VQS

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3 VL 2B Instruct	0K / 4.3 GB	2204577	448
Qwen3 VL Reranker 2B	0K / 4.3 GB	764323	212
PhysBrain1.5 2B	0K / 4.3 GB	272	13
Qevi 2B	0K / 4.3 GB	61	2
Qwen3 VL 2B Instruct FP8	0K / 3.5 GB	65063	43
Typhoon Ocr1.5 2B	0K / 4.3 GB	55029	25
Foresight Qwen3vl 2B Sft	0K / 4.3 GB	54	1
...hlighter Qwen3 Vl 2B Rl Merged	0K / 3.3 GB	22	1
SingGuard 2B	0K / 4.3 GB	747	7
ImageShield MMCF 2B Vl	0K / 4.3 GB	33	1

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