What are the hardware requirements for Qwen2.5 VL 7B Instruct GPTQ Safetensors?

Qwen2.5 VL 7B Instruct GPTQ Safetensors requires approximately 5.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen2.5 VL 7B Instruct GPTQ Safetensors and how large is it?

Qwen2.5 VL 7B Instruct GPTQ Safetensors is developed by simaai, 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 Qwen2.5 VL 7B Instruct GPTQ Safetensors?

Qwen2.5 VL 7B Instruct GPTQ Safetensors is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 VL 7B Instruct GPTQ Safetensors by simaai — VRAM 5.4GB

Name: Qwen2.5 VL 7B Instruct GPTQ Safetensors
Author: simaai

Qwen2.5 VL 7B Instruct GPTQ Safetensors is an open-source language model by simaai. Features: 7b LLM, VRAM: 5.4GB, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.25.

Base model:quantized:qwen/qwen... Base model:qwen/qwen2.5-vl-7b-... Compressed-tensors Conversational Endpoints compatible Gptq Image-text-to-text Instruct Multilingual Quantized Qwen2 5 vl Region:us Safetensors Sima-ai

Model Card on HF 🤗: https://huggingface.co/simaai/Qwen2.5-VL-7B-Instruct-GPTQ-Safetensors

Qwen2.5 VL 7B Instruct GPTQ Safetensors Parameters and Internals

LLM Name	Qwen2.5 VL 7B Instruct GPTQ Safetensors
Repository 🤗	https://huggingface.co/simaai/Qwen2.5-VL-7B-Instruct-GPTQ-Safetensors
Base Model(s)	Qwen/Qwen2.5-VL-7B-Instruct Qwen/Qwen2.5-VL-7B-Instruct
Model Size	7b
Required VRAM	5.4 GB
Updated	2026-10-22
Maintainer	simaai
Model Type	qwen2_5_vl
Instruction-Based	Yes
Model Files	5.4 GB
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	Qwen2_5_VLForConditionalGeneration
License	apache-2.0
Model Max Length	131072
Transformers Version	5.10.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Qwen2.5 VL 7B Instruct GPTQ Safetensors 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 Qwen2.5 VL 7B Instruct GPTQ Safetensors

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OlmOCR 2 7B 1025 Mlx 8bit	125K / 9.4 GB	172	2
OlmOCR 2 7B 1025 Mlx 4bit	125K / 5.6 GB	126	1
OlmOCR 7B 0725 8bit	125K / 9.4 GB	97	5
Qwen2.5 VL 7B Instruct 4bit	125K / 5.6 GB	3486	4
OlmOCR 7B 0725 4bit	125K / 5.6 GB	23	1
Qwen2.5 VL 7B Instruct 8bit	125K / 8.9 GB	1759	17
Jedi 7B 1080p 4bit	125K / 4.9 GB	19	1
Jedi 7B 1080p 6bit	125K / 6.9 GB	19	1
Qwen2.5 VL 7B Instruct 6bit	125K / 6.9 GB	107	3
Qwen2.5 VL 7B Instruct 3bit	125K / 4.7 GB	56	1