Qwen/Qwen2-VL-7B-Instruct-AWQ
image-text-to-text model by Qwen
From the publisher
Model card & documentation
Source previewRead the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.
We're excited to unveil Qwen2-VL, the latest iteration of our Qwen-VL model, representing nearly a year of innovation. We have three models with 2, 7 and 72 billion parameters. This repo contains the instruction-tuned 7B Qwen2-VL model. For more information, visit our Blog and GitHub. This section reports the generation performance of quantized models (including GPTQ and AWQ) of the Qwen2-VL series. Specifically, we report: We use VLMEvalkit to evaluate all models. This section reports the speed performance of bf16 models, quantized models (including GPTQ-Int4, GPTQ-Int8 and AWQ) of the Qwen2-VL series. Specifically, we report the inference speed (tokens/s) as well as memory footprint (GB) under the conditions of different context lengths. The environment of the evaluation with huggingface transformers is: Note: The code of Qwen2-VL has been in the latest Hugging face transformers and we advise you to build from source with command pip install git+https://github.com/huggingface/transformers, or you might…
Read the full model card ↗ · Preview checked 2026-10-29T16:59:33.243Z
Inside the original model card — Document outline
- Qwen2-VL-7B-Instruct-AWQ
- Introduction
- What’s New in Qwen2-VL?
- Key Enhancements:
- Model Architecture Updates:
- Benchmark
- Performance of Quantized Models
- Speed Benchmark
- Requirements
- Quickstart
- More Usage Tips
- Image Resolution for performance boost
Headings are captured from the source. Links open the publisher’s document, not a locally hosted copy.
Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
Qwen/Qwen2-VL-7B-Instruct-AWQ is a image-text-to-text model repository published by Qwen on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- image-text-to-text
- Library
- transformers
- Recent downloads (30 days)
- 1,090,341
- Cumulative likes
- 58
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 8,291,375,616
- Architecture
- Qwen2VLForConditionalGeneration
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2024-08-29T02:42:15.000Z
- Last modified
- 2024-09-25T12:32:39.000Z
Compatibility and lineage
Reported languages: en
Reported base models: Qwen/Qwen2-VL-7B-Instruct
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
Check license terms and access requirements first. Review the model card’s documented loading instructions, evaluations and safety limitations. Benchmark scores are not imported by this directory, and popularity is not an accuracy ranking.
No model weights are downloaded or executed by AltAPIs. Never enable remote model code without reviewing it.
Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-01T06:51:30.840Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.