Moondream3 Preview Point

Moondream3 Preview Point

Playground

Moondream3 Point finds objects in images and returns precise coordinate points for computer vision tasks, enabling accurate point localization. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Moondream 3 — Point (Locate & Describe)

Moondream 3 Point is a vision-language model designed to identify and describe specific objects within an image using natural language. Instead of returning coordinates, it provides a concise textual description of the detected object, making it ideal for lightweight interactive queries and content understanding.

✨ Key Features

• Locate and Describe Objects Enter a short text query (e.g., “hat”, “watch”, “phone”) and receive a natural-language description of that item in context.

• Fast Single-Object Queries Optimized for fast, low-latency inference — perfect for real-time applications.

• Readable Natural Output The model outputs a fluent English sentence describing the object’s appearance, position, and context.

• Multilingual Understanding Capable of recognizing and describing objects in a wide range of visual scenarios.

⚙️ Example Usage

Locate & Describe “Hat”

{
  "image": "https://example.com/photo.jpg",
  "prompt": "hat"
}

Example Response

{
  "answer": "The woman is wearing a pink baseball cap with a strap across her forehead. She is also wearing large silver hoop earrings and a pink fuzzy sweater."
}

💡 Best Practices

• Use concise object names (e.g., “hat”, “car”, “tree”) for more accurate detection.

• For precise bounding boxes or coordinates, use:

  • Moondream 3 Detect — returns x_min, y_min, x_max, y_max bounding boxes.
  • A coordinate-enabled version of Moondream 3 Point (coming soon).

• Supported formats: JPEG, PNG, WebP

• Maximum image size: 10 MB

💰 Pricing

• $0.001 per request
• Volume and enterprise pricing available upon request.

📝 Notes

• The current endpoint returns descriptive text in JSON format:

  {"answer": "..."}

  — it does not output coordinates.

• For small or occluded objects, use higher-resolution input or switch to the Detect model for better spatial precision.

# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/moondream3-preview/point" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "enable_sync_mode": true
}'

# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"