Two images can look similar while telling different stories.
OGAD (Off Grid AI Desktop) lets you attach multiple images to a local vision chat and ask for a structured comparison. Compare two design drafts, two photos of a workspace or two versions of a diagram without uploading them to a cloud AI service. Download the app and a compatible local vision model before going offline.
Download OGAD for Mac or Windows
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Give the model a clear comparison task
Start with two images. Say which is A and which is B using visible details, such as “A has a blue header; B has a white header.” That is more reliable than assuming a model will infer your labels.
Compare these two images. A has a blue header; B has a white header. List visible differences in layout, text and spacing. Separate observations from suggestions, and say when a detail is too small to read.
The useful result is a first draft you can check. You supply the image and the question; the model supplies an answer for review.
Choose a model that can read images
Open Models and choose a local vision-capable model that fits your computer. The chat interface identifies options such as Qwen3-VL 2B or Gemma E4B when image support is missing. Download the complete model and its required vision component, then select it for the chat.
A text-only model cannot inspect the image. An image-generation model creates pictures; it is not the model you need for this analysis. Local chat and vision are part of OGAD’s free desktop app.
Use the model recommendations shown for your hardware. The installed file size is not the amount of working memory the model needs while answering. If a large model cannot load, choose a smaller supported vision option and close other heavy applications.
Get your first answer
- Save both images locally. Keep a clear A/B description ready.
- In OGAD, open Chat and select the downloaded local vision model.
- Open the + composer menu and select Add image.
- Choose both files and check the attachment previews.
- Send the example question above, adapted to your images.
- Compare the answer with both originals before you reuse it.
The image picker supports multiple files, but begin with two rather than a large collection. Extra images consume context and memory, and make it harder to check which image a statement describes.
Use a comparison brief with a clear acceptance check
Suppose you have two versions of a presentation title slide. Both use the same heading, but one places the image behind the text and the other puts it beside the text. Your question is whether the title remains easy to read, not which design the model “likes” more.
Attach both images, describe a visible identifying feature for each, and ask:
Compare title visibility, spacing around the title, and interference from the image. For each observation, identify A or B and the visible detail that supports it. Keep aesthetic suggestions in a separate section.
Check the observations against the originals. If the model says one title is larger, inspect it yourself rather than treating that as a pixel measurement. If it cannot read a word, provide a closer crop instead of accepting a guessed spelling.
Then make one decision you can act on: move the image, add space, or change the title placement in your actual slide editor. Ask about the revised pair only after exporting the new slide images. The model does not see changes you have made elsewhere until you supply them.
This process also works for before-and-after room photos or two diagram drafts. Choose the visible property you care about first. Do not ask a still-image comparison to establish hidden facts such as whether a button works or whether a layout passed an accessibility test.
For exact dimensions, color values or every changed pixel, use a dedicated image tool. A vision comparison can miss small changes or describe differences that are not present.
Keep the analysis on your computer
Select the local model and use files already on your computer. You can disconnect internet access after setup and send a short image question to check the local route. A remote model or an online tool changes that data path, so leave those out of this workflow.
Local analysis avoids sending the image to a cloud AI provider. Separate file backup and device-sync settings still apply if you have enabled them.
When the answer is not useful
| Symptom | Useful next step |
|---|---|
| Image input is unavailable | Select a vision model and complete its required downloads |
| Small text is misread | Attach a sharper crop of the relevant area |
| The answer is vague | Ask about one visible detail or one concrete decision |
| The model invents details | Request visible evidence and verify it against the source |
| The model cannot load | Try a smaller supported model that fits available memory |
These steps use the image-input workflow in OGAD 0.0.51. Keep the app current and use a complete local model.
Try it with your own image
Download OGAD, choose a vision model and compare two drafts against one clear design question. Keep the source beside the answer. You get a useful starting point while the image stays within your local analysis workflow.