FACE DETECTION API
Detect faces with a single API call.
Send a photo and a question, get faces, bounding boxes, age estimates and expressions back as JSON, from vision-language models on the chat API.
Hand this to your agent
Add a Runcrate model to this project: run curl -fsSL"https://runcrate.ai/agents.md?intent=build"and follow it.
Your agent asks for an API key. Create a key
Quick start
Hand it to your agent. Or read the request it sends.
Your agent writes and runs it. The same key works for every model and every GPU.
Available models
Models you can call today. Billed prices, as charged.
| Model | Maker | Price | Detail |
|---|---|---|---|
| Qwen/Qwen3-VL-235B-A22B-Instruct | Alibaba | $0.21 in, $0.924 out per 1M tokens | 235B MoE, detailed visual understanding |
| Qwen/Qwen3-VL-30B-A3B-Instruct | Alibaba | $0.158 in, $0.63 out per 1M tokens | 30B MoE, efficient processing |
Why Runcrate
Built for production. One key, one balance.
Vision-language detection
Use the full power of vision-language models for face detection. Ask for bounding boxes, age estimates, expressions, or any custom attribute in natural language.
Structured output
Request JSON-formatted results with bounding boxes, confidence scores, and attributes. Parse programmatically for integration into your pipeline.
No specialized library
Skip OpenCV, dlib, and MediaPipe setup. Use the same chat completions API you already use for text, with an image added.
Custom analysis
Beyond detection: ask the model to analyze facial expressions, estimate demographics, count people, or describe the scene context around each face.
FAQ