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Judge Images (Vision QA)
x402
Judge Images (Vision QA) is a paid API for AI agents from agent402.tools, paid per call via x402, $0.003/call, status unknown (last checked 2026-10-16).
Ask structured questions about up to 4 images and receive machine-branchable answers (yes/no probability, multiple choice, score, or bounding box) powered by the Jev vision model.
Price / call$0.003
Success—
StatusUnknown
How this service works
Ask typed questions about up to 4 images (PNG or JPEG) and get answers your code can branch on: noul (yes/no probability), choice, score, and box (where something is, as edges from 0 to 1). Name each image, then refer to it as `name` in a question. Preview: built on Jev features its maker labels experimental. Answers come from a model, not deterministic code.
Output
Returns structured answers keyed by your question IDs: 'noul' questions return a probability (0–1) of yes; 'choice' questions return the selected option; 'score' questions return a numeric value; 'box' questions return four edge values (top, right, bottom, left) each from 0 to 1 indicating where the target is located in the image. Answers are model-generated and not deterministic.
Example use cases
Content moderation for uploaded photos
“I have a user-uploaded PNG image called 'profile_pic'. Can you check whether it contains nudity — give me a yes/no probability — and also score how professional-looking it is from 0 to 1?”
UI screenshot element detection
“Here's a screenshot of our app (JPEG, named 'screen'). Is the 'Submit' button visible in it? Give me a yes/no probability, and if it's there, return its bounding box so I know exactly where it is on screen.”
Receipt field verification
“I've got a scanned receipt image (PNG, named 'receipt'). Ask it whether the total amount is greater than $50 — yes or no — and which payment method is shown: cash, card, or other?”
Technical details
Endpoint
POSThttps://agent402.tools/v1/judge/vision?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need programmatically branchable answers about image content — particularly when you need structured output types like probabilities, scores, or bounding boxes rather than free-form captions. It is ideal for automated pipelines that need to make code-level decisions based on visual content (e.g., content moderation, UI testing, document verification). Prefer it over general vision LLM calls when you need consistent, typed answer formats your code can reliably parse and branch on.
Side effects
- Image exceeds 4 MiB or dimensions outside 256–1568 px range — request rejected
- More than 4 images provided — validation error
- Invalid question type specified (not noul/choice/score/box) — schema error
- Model returns ambiguous or low-confidence answer for visually unclear images
- Box question automatically routes to jev-preview even if jev-latest was requested
- Base64 encoding malformed or format mismatch (png vs jpeg) — parsing error
- Context string exceeds 8000 characters — truncation or rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| model | string | jev-latest is the tested Jev version; a box question always runs on jev-preview. |
| state | — | Optional text context, up to 8000 characters. |
| images | object | Your own names mapped to { format: "png" | "jpeg", data_base64 }. Up to 4; each side 256 to 1568 px, 4 MiB each. Images are not resized. |
| questions | object | Your own ids mapped to { type: noul | choice | score | box, instructions, criteria }. Refer to an image as `name` in backticks. |
Tags
x402
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