Nano Banana 2.1 is LIVE — Google's Latest | Try Now →

wavespeed-ai/sam3-image

SAM 3 is a unified foundation model for promptable image segmentation using text, points, or boxes to detect and segment objects. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Image Tools
Input

Drag & drop or click to upload

preview
Whether to overlay the segmentation mask on the original image

Idle

the man

$0.005per run·~200 / $1

Next:

ExamplesView all

the man

the man

the person

the person

the woman

the woman

the man

the man

the boat

the boat

Related Models

README

SAM3 Image Segmentation

SAM3 Image Segmentation segments target objects in an image using flexible prompt inputs. Provide an image and use a text prompt, point prompts, box prompts, or a combination of them to generate a precise segmentation result for the selected subject.

Why Choose This?

  • Image segmentation workflow
    Segment people, objects, animals, backgrounds, or other visible targets from a source image.

  • Multiple prompt types
    Use text prompts, point prompts, box prompts, or combined prompt guidance for more accurate targeting.

  • Text-based target selection
    Describe what to segment with natural language, such as the man, the car, or background.

  • Point and box control
    Use coordinates or bounding boxes when you need more precise target selection.

  • Mask output control
    Use apply_mask to choose whether the mask is applied to the image or returned as a black-and-white mask-style output.

  • Low-cost segmentation
    Generate segmentation outputs at a fixed price per image.

Parameters

ParameterRequiredDescription
imageYesSource image to segment. Upload an image or provide a public image URL.
promptConditionalText description of the target object or region to segment.
point_promptsConditionalPoint coordinates used to identify the target object or region.
box_promptsConditionalBounding box coordinates used to identify the target object or region.
apply_maskNoWhether to apply the mask to the original image. When disabled, the output is a mask-style image with a black background and the selected region in white.
output_formatNoOutput image format: jpeg, png, or webp. Default: png.

At least one prompt type must be provided: prompt, point_prompts, or box_prompts.

How to Use

  1. Upload an image — Provide the source image you want to segment.
  2. Add a target prompt — Use a text prompt, point prompts, box prompts, or a combination of them.
  3. Choose mask behavior — Enable apply_mask to apply the mask to the image. Disable it when you need a black-and-white mask output.
  4. Choose output format — Select jpeg, png, or webp.
  5. Submit — Generate the segmentation result.

Pricing

Pricing is fixed at $0.005 per image.

OutputCost
One segmented image$0.005

Image size, prompt type, apply_mask, and output_format do not add separate charges.

Best Use Cases

  • Object segmentation — Segment people, products, animals, vehicles, clothing, or props.
  • Background workflows — Target foreground subjects or background regions for downstream editing.
  • Mask generation — Create black-and-white mask-style outputs for compositing or image editing.
  • Object isolation — Isolate selected objects for design, marketing, or post-production workflows.
  • Data annotation — Generate segmentation masks for dataset preparation or labeling workflows.
  • E-commerce assets — Segment products for catalog images, ads, and layout workflows.

Pro Tips

  • Use short, concrete text prompts such as person, dog, car, or background.
  • Use point prompts when text alone is ambiguous.
  • Use box prompts when you need to constrain segmentation to a specific region.
  • Combine text, points, and boxes when the target is difficult to isolate.
  • Use apply_mask=true when you want the mask applied to the original image.
  • Use apply_mask=false when you need a black-background mask output with the selected region shown in white.
  • Use png when working with mask or compositing workflows.

Notes

  • image is required.
  • At least one of prompt, point_prompts, or box_prompts must be provided.
  • Point and box prompts use image coordinates.
  • When apply_mask is disabled, the output is a mask-style image with a black background and the selected region in white.
  • output_format defaults to png.

Related Models

Note:This website uses AI models provided by third parties. Documentation prices are for reference and may be outdated. The Generate button shows an estimate; the final task charge prevails.

Sam3 Image API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/sam3-image with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Sam3 Image below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
    "apply_mask": true,
    "output_format": "png"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/sam3-image" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d "$REQUEST_BODY")

TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
    -H "Authorization: Bearer $WAVESPEED_API_KEY")
  RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
  STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
  case "$STATUS" in
    completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout|deleted) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    *) sleep 2 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/wavespeed-ai/sam3-image";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');

async function requestJson(url, options = {}) {
  const response = await fetch(url, options);
  if (!response.ok) throw new Error(await response.text());
  return response.json();
}

// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
        "apply_mask": true,
        "output_format": "png"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;

// 2. Poll until the prediction finishes.
while (true) {
  const resultBody = await requestJson(resultUrl, {
    headers: { "Authorization": `Bearer ${apiKey}` },
  });
  const result = resultBody.data ?? resultBody;
  if (result.status === "completed") {
    console.log(result.outputs);
    break;
  }
  if (["failed", "cancelled", "timeout", "deleted"].includes(result.status)) throw new Error(JSON.stringify(result));
  await new Promise(resolve => setTimeout(resolve, 2000));
}
Python example
import json
import os
import time
from urllib.request import Request, urlopen

api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
    "apply_mask": True,
    "output_format": "png"
}

def request_json(url, data=None):
    request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
    with urlopen(request) as response:
        return json.load(response)

# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/wavespeed-ai/sam3-image", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
    raise RuntimeError("Submission response did not contain a prediction id")
result_url = f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"

# 2. Poll until the prediction finishes.
while True:
    result_body = request_json(result_url)
    result = result_body.get("data", result_body)
    status = result.get("status")
    if status == "completed":
        print(result.get("outputs", []))
        break
    if status in {"failed", "cancelled", "timeout", "deleted"}:
        raise RuntimeError(result)
    time.sleep(2)

Sam3 Image API — Frequently asked questions

What is the Sam3 Image API?

Sam3 Image is a WaveSpeedAI model for image processing, exposed as a REST API on WaveSpeedAI. SAM 3 is a unified foundation model for promptable image segmentation using text, points, or boxes to detect and segment objects. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Sam3 Image API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID. Poll the result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates Python, JavaScript, and cURL examples for submitting requests and polling results. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/sam3-image.

How much does Sam3 Image cost per run?

Sam3 Image starts at $0.005 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does Sam3 Image accept?

Key inputs: `prompt`, `image`, `apply_mask`, `box_prompts`, `output_format`, `point_prompts`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/wavespeed-ai/sam3-image.

How long does Sam3 Image take to generate?

Reported generation time on WaveSpeedAI is around 3 seconds per request. This is an estimate, not a latency guarantee; queue time and input settings can change the total wait. live status is visible in the prediction record.

Can I use Sam3 Image outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). Check the provider's applicable terms and WaveSpeedAI's Terms of Service before commercial use.

llms.txt — wavespeed-ai/sam3-image for AI agents and LLMs