What are the hardware requirements for Qwen2 VL 2B Instruct AWQ?

Qwen2 VL 2B Instruct AWQ requires approximately 3 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen2 VL 2B Instruct AWQ and how large is it?

Qwen2 VL 2B Instruct AWQ is developed by Qwen, 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 Qwen2 VL 2B Instruct AWQ?

Qwen2 VL 2B Instruct AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2 VL 2B Instruct AWQ by Qwen — VRAM 3GB, 32K context

Name: Qwen2 VL 2B Instruct AWQ
Author: Qwen

Qwen2 VL 2B Instruct AWQ is an open-source language model by Qwen. Features: 2b LLM, VRAM: 3GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.17.

Arxiv:2308.12966 Arxiv:2409.12191 4-bit Awq Base model:quantized:qwen/qwen... Base model:qwen/qwen2-vl-2b-in... Conversational En Image-text-to-text Instruct Multimodal Quantized Qwen2 vl Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/Qwen/Qwen2-VL-2B-Instruct-AWQ

Qwen2 VL 2B Instruct AWQ Parameters and Internals

Model Type

text generation, multimodal

Use Cases

Areas:

Research, Commercial applications

Applications:

Visual understanding, Video-based question answering, Dialog, Content creation

Primary Use Cases:

Operates mobile devices, Interacts with robots

Limitations:

Lack of Audio Support, Limited Capacity for Complex Instruction, Weak Spatial Reasoning Skills

Considerations:

The model's limitations mentioned above.

Supported Languages

English (Full proficiency), Chinese (Full proficiency), European languages (Supported), Japanese (Supported), Korean (Supported), Arabic (Supported), Vietnamese (Supported)

Input Output

Input Format:

Messages with roles and content (image, video, text)

Accepted Modalities:

image, video, text

Output Format:

Generated text output

Performance Tips:

Enable flash_attention_2 for better acceleration and memory saving.

Release Notes

Version:

Notes:

Includes multimodal capabilities and supports various visual understanding tasks.

LLM Name	Qwen2 VL 2B Instruct AWQ
Repository 🤗	https://huggingface.co/Qwen/Qwen2-VL-2B-Instruct-AWQ
Base Model(s)	Qwen2 VL 2B Instruct Qwen/Qwen2-VL-2B-Instruct
Model Size	2b
Required VRAM	3 GB
Updated	2026-08-07
Maintainer	Qwen
Model Type	qwen2_vl
Instruction-Based	Yes
Model Files	3.0 GB
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	Qwen2VLForConditionalGeneration
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.45.0.dev0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	float16
Errors	replace

Rank the Qwen2 VL 2B Instruct AWQ 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 VL 2B Instruct AWQ

Best Alternatives	Context / RAM	Downloads	Likes
...L 2B Instruct Unsloth Bnb 4bit	32K / 2.5 GB	2312	7
Qwen2 VL 2B Instruct 4bit	32K / 1.2 GB	3899	7
Qwen2 VL 2B Instruct Bnb 4bit	32K / 1.5 GB	1605	1
Qwen2 VL 2B Instruct 8bit	32K / 2.4 GB	99	2
ShowUI 2B	32K / 4.4 GB	3756	279
Qwen2 VL 2B Instruct	32K / 4.4 GB	925	5
Qwen2 VL 2B Instruct GPTQ Int4	32K / 2.5 GB	793	28
Qwen2 VL 2B Instruct GPTQ Int8	32K / 3.1 GB	471	17
Qwen2 VL 2B Instruct Bf16	32K / 4.4 GB	90	1
Qwen2 VL 2B Instruct	32K / 4.4 GB	3	24

Note: green Score (e.g. "73.2") means that the model is better than Qwen/Qwen2-VL-2B-Instruct-AWQ.