CivArchive
    Qwen2.5-VL - 7b
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    Preview 135345059

    Introduction

    In the past five months since Qwen2-VL’s release, numerous developers have built new models on the Qwen2-VL vision-language models, providing us with valuable feedback. During this period, we focused on building more useful vision-language models. Today, we are excited to introduce the latest addition to the Qwen family: Qwen2.5-VL.

    Key Enhancements:

    • Understand things visually: Qwen2.5-VL is not only proficient in recognizing common objects such as flowers, birds, fish, and insects, but it is highly capable of analyzing texts, charts, icons, graphics, and layouts within images.

    • Being agentic: Qwen2.5-VL directly plays as a visual agent that can reason and dynamically direct tools, which is capable of computer use and phone use.

    • Understanding long videos and capturing events: Qwen2.5-VL can comprehend videos of over 1 hour, and this time it has a new ability of cpaturing event by pinpointing the relevant video segments.

    • Capable of visual localization in different formats: Qwen2.5-VL can accurately localize objects in an image by generating bounding boxes or points, and it can provide stable JSON outputs for coordinates and attributes.

    • Generating structured outputs: for data like scans of invoices, forms, tables, etc. Qwen2.5-VL supports structured outputs of their contents, benefiting usages in finance, commerce, etc.

    Model Architecture Updates:

    • Dynamic Resolution and Frame Rate Training for Video Understanding:

    We extend dynamic resolution to the temporal dimension by adopting dynamic FPS sampling, enabling the model to comprehend videos at various sampling rates. Accordingly, we update mRoPE in the time dimension with IDs and absolute time alignment, enabling the model to learn temporal sequence and speed, and ultimately acquire the ability to pinpoint specific moments.

    Description

    VisionLanguage
    Qwen
    by CivitaiOfficial
    Download (Beta) View on CivitAI
    base model

    Details

    Downloads
    2
    Platform
    CivitAI
    Platform Status
    Available
    Created
    7/9/2026
    Updated
    7/11/2026
    Deleted
    -

    Files

    qwen25VL_7b.safetensors

    Size:
    15.45 GB
    SHA256:
    cfafd739459bc86257397259f612a9aee88e5b98e85b5c0d0d1717e898b3463a

    Mirrors

    HuggingFace (28 mirrors)
    CivitAI (1 mirrors)
    ModelScope (1 mirrors)
    ModelScope CN (1 mirrors)

    qwen25VL_7b.safetensors

    Size:
    8.74 GB
    SHA256:
    cb5636d852a0ea6a9075ab1bef496c0db7aef13c02350571e388aea959c5c0b4

    Mirrors

    HuggingFace (85 mirrors)
    CivitAI (5 mirrors)
    ModelScope (1 mirrors)
    ModelScope CN (2 mirrors)

    qwen25VL_7b.safetensors

    Size:
    5.69 GB
    SHA256:
    c7bb24d331f5df991bab2ce76a15195b12652e86a69a79823183c6a047407463

    Mirrors

    CivitAI (1 mirrors)