Upscale an image

Upscale an image to a higher resolution (all 4 models)

curl --request POST \
  --url https://api.samsa.ai/public/v1/images/upscales \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "image": {
    "image_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
    "url": "https://cdn.example.com/photo.png",
    "base64": "<string>",
    "mime_type": "image/png"
  },
  "model": "crystal",
  "options": {
    "magnific_creative": {
      "prompt": "",
      "optimized_for": "standard",
      "creativity": 0,
      "hdr": 0,
      "resemblance": 0,
      "fractality": 0,
      "engine": "automatic"
    },
    "magnific_precision": {
      "sharpen": 7,
      "smart_grain": 7,
      "ultra_detail": 30,
      "flavor": "sublime"
    }
  },
  "webhook_url": "https://example.com/webhooks/samsa"
}
'

import requests

url = "https://api.samsa.ai/public/v1/images/upscales"

payload = {
    "image": {
        "image_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
        "url": "https://cdn.example.com/photo.png",
        "base64": "<string>",
        "mime_type": "image/png"
    },
    "model": "crystal",
    "options": {
        "magnific_creative": {
            "prompt": "",
            "optimized_for": "standard",
            "creativity": 0,
            "hdr": 0,
            "resemblance": 0,
            "fractality": 0,
            "engine": "automatic"
        },
        "magnific_precision": {
            "sharpen": 7,
            "smart_grain": 7,
            "ultra_detail": 30,
            "flavor": "sublime"
        }
    },
    "webhook_url": "https://example.com/webhooks/samsa"
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    image: {
      image_id: '3c90c3cc-0d44-4b50-8888-8dd25736052a',
      url: 'https://cdn.example.com/photo.png',
      base64: '<string>',
      mime_type: 'image/png'
    },
    model: 'crystal',
    options: {
      magnific_creative: {
        prompt: '',
        optimized_for: 'standard',
        creativity: 0,
        hdr: 0,
        resemblance: 0,
        fractality: 0,
        engine: 'automatic'
      },
      magnific_precision: {sharpen: 7, smart_grain: 7, ultra_detail: 30, flavor: 'sublime'}
    },
    webhook_url: 'https://example.com/webhooks/samsa'
  })
};

fetch('https://api.samsa.ai/public/v1/images/upscales', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.samsa.ai/public/v1/images/upscales",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'image' => [
        'image_id' => '3c90c3cc-0d44-4b50-8888-8dd25736052a',
        'url' => 'https://cdn.example.com/photo.png',
        'base64' => '<string>',
        'mime_type' => 'image/png'
    ],
    'model' => 'crystal',
    'options' => [
        'magnific_creative' => [
                'prompt' => '',
                'optimized_for' => 'standard',
                'creativity' => 0,
                'hdr' => 0,
                'resemblance' => 0,
                'fractality' => 0,
                'engine' => 'automatic'
        ],
        'magnific_precision' => [
                'sharpen' => 7,
                'smart_grain' => 7,
                'ultra_detail' => 30,
                'flavor' => 'sublime'
        ]
    ],
    'webhook_url' => 'https://example.com/webhooks/samsa'
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.samsa.ai/public/v1/images/upscales"

	payload := strings.NewReader("{\n  \"image\": {\n    \"image_id\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n    \"url\": \"https://cdn.example.com/photo.png\",\n    \"base64\": \"<string>\",\n    \"mime_type\": \"image/png\"\n  },\n  \"model\": \"crystal\",\n  \"options\": {\n    \"magnific_creative\": {\n      \"prompt\": \"\",\n      \"optimized_for\": \"standard\",\n      \"creativity\": 0,\n      \"hdr\": 0,\n      \"resemblance\": 0,\n      \"fractality\": 0,\n      \"engine\": \"automatic\"\n    },\n    \"magnific_precision\": {\n      \"sharpen\": 7,\n      \"smart_grain\": 7,\n      \"ultra_detail\": 30,\n      \"flavor\": \"sublime\"\n    }\n  },\n  \"webhook_url\": \"https://example.com/webhooks/samsa\"\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.samsa.ai/public/v1/images/upscales")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"image\": {\n    \"image_id\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n    \"url\": \"https://cdn.example.com/photo.png\",\n    \"base64\": \"<string>\",\n    \"mime_type\": \"image/png\"\n  },\n  \"model\": \"crystal\",\n  \"options\": {\n    \"magnific_creative\": {\n      \"prompt\": \"\",\n      \"optimized_for\": \"standard\",\n      \"creativity\": 0,\n      \"hdr\": 0,\n      \"resemblance\": 0,\n      \"fractality\": 0,\n      \"engine\": \"automatic\"\n    },\n    \"magnific_precision\": {\n      \"sharpen\": 7,\n      \"smart_grain\": 7,\n      \"ultra_detail\": 30,\n      \"flavor\": \"sublime\"\n    }\n  },\n  \"webhook_url\": \"https://example.com/webhooks/samsa\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.samsa.ai/public/v1/images/upscales")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"image\": {\n    \"image_id\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n    \"url\": \"https://cdn.example.com/photo.png\",\n    \"base64\": \"<string>\",\n    \"mime_type\": \"image/png\"\n  },\n  \"model\": \"crystal\",\n  \"options\": {\n    \"magnific_creative\": {\n      \"prompt\": \"\",\n      \"optimized_for\": \"standard\",\n      \"creativity\": 0,\n      \"hdr\": 0,\n      \"resemblance\": 0,\n      \"fractality\": 0,\n      \"engine\": \"automatic\"\n    },\n    \"magnific_precision\": {\n      \"sharpen\": 7,\n      \"smart_grain\": 7,\n      \"ultra_detail\": 30,\n      \"flavor\": \"sublime\"\n    }\n  },\n  \"webhook_url\": \"https://example.com/webhooks/samsa\"\n}"

response = http.request(request)
puts response.read_body

{
  "id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
  "estimated_credits": 123
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

POST

images

upscales

Upscale an image to a higher resolution (all 4 models)

curl --request POST \
  --url https://api.samsa.ai/public/v1/images/upscales \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "image": {
    "image_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
    "url": "https://cdn.example.com/photo.png",
    "base64": "<string>",
    "mime_type": "image/png"
  },
  "model": "crystal",
  "options": {
    "magnific_creative": {
      "prompt": "",
      "optimized_for": "standard",
      "creativity": 0,
      "hdr": 0,
      "resemblance": 0,
      "fractality": 0,
      "engine": "automatic"
    },
    "magnific_precision": {
      "sharpen": 7,
      "smart_grain": 7,
      "ultra_detail": 30,
      "flavor": "sublime"
    }
  },
  "webhook_url": "https://example.com/webhooks/samsa"
}
'

import requests

url = "https://api.samsa.ai/public/v1/images/upscales"

payload = {
    "image": {
        "image_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
        "url": "https://cdn.example.com/photo.png",
        "base64": "<string>",
        "mime_type": "image/png"
    },
    "model": "crystal",
    "options": {
        "magnific_creative": {
            "prompt": "",
            "optimized_for": "standard",
            "creativity": 0,
            "hdr": 0,
            "resemblance": 0,
            "fractality": 0,
            "engine": "automatic"
        },
        "magnific_precision": {
            "sharpen": 7,
            "smart_grain": 7,
            "ultra_detail": 30,
            "flavor": "sublime"
        }
    },
    "webhook_url": "https://example.com/webhooks/samsa"
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    image: {
      image_id: '3c90c3cc-0d44-4b50-8888-8dd25736052a',
      url: 'https://cdn.example.com/photo.png',
      base64: '<string>',
      mime_type: 'image/png'
    },
    model: 'crystal',
    options: {
      magnific_creative: {
        prompt: '',
        optimized_for: 'standard',
        creativity: 0,
        hdr: 0,
        resemblance: 0,
        fractality: 0,
        engine: 'automatic'
      },
      magnific_precision: {sharpen: 7, smart_grain: 7, ultra_detail: 30, flavor: 'sublime'}
    },
    webhook_url: 'https://example.com/webhooks/samsa'
  })
};

fetch('https://api.samsa.ai/public/v1/images/upscales', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.samsa.ai/public/v1/images/upscales",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'image' => [
        'image_id' => '3c90c3cc-0d44-4b50-8888-8dd25736052a',
        'url' => 'https://cdn.example.com/photo.png',
        'base64' => '<string>',
        'mime_type' => 'image/png'
    ],
    'model' => 'crystal',
    'options' => [
        'magnific_creative' => [
                'prompt' => '',
                'optimized_for' => 'standard',
                'creativity' => 0,
                'hdr' => 0,
                'resemblance' => 0,
                'fractality' => 0,
                'engine' => 'automatic'
        ],
        'magnific_precision' => [
                'sharpen' => 7,
                'smart_grain' => 7,
                'ultra_detail' => 30,
                'flavor' => 'sublime'
        ]
    ],
    'webhook_url' => 'https://example.com/webhooks/samsa'
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.samsa.ai/public/v1/images/upscales"

	payload := strings.NewReader("{\n  \"image\": {\n    \"image_id\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n    \"url\": \"https://cdn.example.com/photo.png\",\n    \"base64\": \"<string>\",\n    \"mime_type\": \"image/png\"\n  },\n  \"model\": \"crystal\",\n  \"options\": {\n    \"magnific_creative\": {\n      \"prompt\": \"\",\n      \"optimized_for\": \"standard\",\n      \"creativity\": 0,\n      \"hdr\": 0,\n      \"resemblance\": 0,\n      \"fractality\": 0,\n      \"engine\": \"automatic\"\n    },\n    \"magnific_precision\": {\n      \"sharpen\": 7,\n      \"smart_grain\": 7,\n      \"ultra_detail\": 30,\n      \"flavor\": \"sublime\"\n    }\n  },\n  \"webhook_url\": \"https://example.com/webhooks/samsa\"\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.samsa.ai/public/v1/images/upscales")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"image\": {\n    \"image_id\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n    \"url\": \"https://cdn.example.com/photo.png\",\n    \"base64\": \"<string>\",\n    \"mime_type\": \"image/png\"\n  },\n  \"model\": \"crystal\",\n  \"options\": {\n    \"magnific_creative\": {\n      \"prompt\": \"\",\n      \"optimized_for\": \"standard\",\n      \"creativity\": 0,\n      \"hdr\": 0,\n      \"resemblance\": 0,\n      \"fractality\": 0,\n      \"engine\": \"automatic\"\n    },\n    \"magnific_precision\": {\n      \"sharpen\": 7,\n      \"smart_grain\": 7,\n      \"ultra_detail\": 30,\n      \"flavor\": \"sublime\"\n    }\n  },\n  \"webhook_url\": \"https://example.com/webhooks/samsa\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.samsa.ai/public/v1/images/upscales")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"image\": {\n    \"image_id\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n    \"url\": \"https://cdn.example.com/photo.png\",\n    \"base64\": \"<string>\",\n    \"mime_type\": \"image/png\"\n  },\n  \"model\": \"crystal\",\n  \"options\": {\n    \"magnific_creative\": {\n      \"prompt\": \"\",\n      \"optimized_for\": \"standard\",\n      \"creativity\": 0,\n      \"hdr\": 0,\n      \"resemblance\": 0,\n      \"fractality\": 0,\n      \"engine\": \"automatic\"\n    },\n    \"magnific_precision\": {\n      \"sharpen\": 7,\n      \"smart_grain\": 7,\n      \"ultra_detail\": 30,\n      \"flavor\": \"sublime\"\n    }\n  },\n  \"webhook_url\": \"https://example.com/webhooks/samsa\"\n}"

response = http.request(request)
puts response.read_body

{
  "id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
  "estimated_credits": 123
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

Upscale one source image to a higher target_resolution with one of four models. The call returns 202 Accepted with a job id; poll GET /images/upscales/{id} for the result. The image takes exactly one of image_id, url, or base64 + mime_type. Requires the images.transform scope.

Example: one source per mode

curl -X POST https://api.samsa.ai/public/v1/images/upscales \
  -H "Authorization: Bearer $SAMSA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "image": { "image_id": "123e4567-e89b-12d3-a456-426614174000" },
    "model": "crystal",
    "target_resolution": "4K"
  }'

curl -X POST https://api.samsa.ai/public/v1/images/upscales \
  -H "Authorization: Bearer $SAMSA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "image": { "url": "https://cdn.example.com/photo.png" },
    "model": "seedvr",
    "target_resolution": "2K"
  }'

curl -X POST https://api.samsa.ai/public/v1/images/upscales \
  -H "Authorization: Bearer $SAMSA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "image": { "base64": "iVBORw0KGgoAAAANSUhEUg...", "mime_type": "image/png" },
    "model": "magnific-precision",
    "target_resolution": "6K",
    "options": { "magnific_precision": { "flavor": "photo", "sharpen": 20, "ultra_detail": 40 } }
  }'

Example: magnific-creative with options

Body

{
  "image": { "image_id": "123e4567-e89b-12d3-a456-426614174000" },
  "model": "magnific-creative",
  "target_resolution": "8K",
  "options": {
    "magnific_creative": {
      "prompt": "sharp studio product photo",
      "optimized_for": "films_n_photography",
      "creativity": 2,
      "hdr": 1,
      "engine": "magnific_sharpy"
    }
  },
  "webhook_url": "https://example.com/webhooks/samsa"
}

The 202 response is the async job handle:

202 Accepted

{
  "id": "d5e6f7a8-9b0c-4d1e-2f3a-4b5c6d7e8f9a",
  "status": "pending",
  "estimated_credits": 75
}

model is crystal (default), seedvr, magnific-creative, or magnific-precision. target_resolution is required and drawn from a closed set: 2K, 4K, 6K, 8K, 10K, 12K, 14K, 16K, 20K, 24K, 28K, 32K, 38K. Classes above 16K are valid for crystal only. The per-model factor and area caps are validated before any credits are charged — an over-cap request is a 422, never a charged job.

options are per-model, typed, and strictly validated: supply magnific_creative for the magnific-creative model or magnific_precision for magnific-precision. seedvr and crystal take no options — supplying options for them is a 422. Unknown keys or out-of-range values are 422.

magnific_creative: prompt (≤ 500 chars), optimized_for (standard · soft_portraits · hard_portraits · art_n_illustration · videogame_assets · nature_n_landscapes · films_n_photography · 3d_renders · science_fiction_n_horror), creativity/hdr/resemblance/ fractality (integers −10…10), engine (automatic · magnific_illusio · magnific_sharpy · magnific_sparkle).
magnific_precision: sharpen/smart_grain/ultra_detail (integers 0…100), flavor (sublime (default) · photo · photo_denoiser).

Credits

Cost is the resolution tier (2K:5, 4K:10, 6K:20, 8K:25, 10K:35, 12K:45, 14K:60, 16K:80) multiplied by the model credit multiplier (Magnific ×3); Crystal above 12K prices by output megapixels. The estimated_credits in the 202 response equals the deduction exactly. See Pricing.

Errors

Status	Code	When
`402`	`insufficient_credits` / `insufficient_team_credits` / `insufficient_unallocated_credits`	The balance this credential can spend is below the job cost. Organizations with at least one active team get the team-aware codes instead of `insufficient_credits` (budget-exempt system organizations excepted). An operational failure inside the deduction can still surface as the generic `insufficient_credits`, whatever the regime.
`402`	`subscription_inactive`	The organization has no usable subscription.
`403`	`missing_scope`	Key lacks the `images.transform` scope.
`404`	`not_found`	The source `image_id` is unknown, or not owned by the API key’s creator — an image another member of your organization created is a `404` too.
`422`	`validation_error`	Zero/multiple source modes, missing/invalid `target_resolution`, an over-cap class, or invalid/misplaced `options`.
`429`	`rate_limited` / `too_many_active_jobs`	Per-key rate window or per-org concurrency cap exceeded.

Authorizations

Authorization

string

header

required

Organization API key as a bearer token: Authorization: Bearer samsa_sk_....

Body

application/json

POST /images/upscales body (SAM-819 / S8.7 — ADR §7, §8, §10).

Upscale ONE source image to a higher target_resolution with one of the four public models. The source is exactly one of image_id (an image in your organization's context), an https url, or base64+mime_type. target_resolution is a CLOSED set — the per-model factor/area caps are validated BEFORE charging (an over-cap request is a 422, never a charged job). options are per-model, typed, and STRICTLY validated (out-of-range / unknown values are 422 — a documented deviation from the app's clamping). Cost is the existing upscale estimator: the resolution tier (2K:5, 4K:10, 6K:20, 8K:25, 10K:35, 12K:45, 14K:60, 16K:80) x the model credit multiplier (Magnific x3); Crystal above 12K prices by output megapixels. estimated_credits in the 202 equals the deduction exactly.

image

PublicImageEditSource · object

required

The source image: exactly one of image_id, an https url, or base64+mime_type.

Show child attributes

target_resolution

enum<string>

required

Target resolution class (REQUIRED) — one of 2K, 4K, 6K, 8K, 10K, 12K, 14K, 16K, 20K, 24K, 28K, 32K, 38K. Classes above 16K are only valid for crystal. The per-model factor/area caps are validated before charging.

Available options:

2K,

4K,

6K,

8K,

10K,

12K,

14K,

16K,

20K,

24K,

28K,

32K,

38K

Example:

"4K"

model

enum<string>

default:crystal

Upscale model: seedvr, crystal (default), magnific-creative, or magnific-precision.

Available options:

seedvr,

crystal,

magnific-creative,

magnific-precision

Example:

"crystal"

options

PublicUpscaleOptions · object | null

Per-model tuning options (typed). Only magnific-creative and magnific-precision accept options — supplying options for seedvr/crystal is a 422.

Show child attributes

webhook_url

string | null

Optional https webhook notified once on terminal status (signed per the webhook signature scheme; see the webhooks docs).

Example:

"https://example.com/webhooks/samsa"

Response

Successful Response

Shared 202 body for the transform-op submits (SAM-813 / S8 wave).

Every POST /images/<op> returns the async job handle {id, status, estimated_credits}. The initial status is pending (the job is queued), with ONE exception: background-removals and vectorizations answer an owned-image_id cache hit (a ready result already exists for that image) with status: "completed" and estimated_credits: 0 — no new job is queued, the completed webhook event is emitted immediately for a supplied webhook_url, and the result is already available from the op's GET .../{id} endpoint. The other transform ops (img2img, variations, resizes, upscales) always start pending.

string<uuid>

required

The job id — poll the op's GET .../{id} endpoint.

status

enum<string>

required

Initial status: pending (job queued — enter the polling flow), or completed with estimated_credits: 0 when background-removals / vectorizations serve an owned-image cache hit (the result is immediately available).

Available options:

pending,

processing,

completed,

failed,

cancelled

Example:

"pending"

estimated_credits

integer

required

Credits this job is expected to cost — 0 on a cache-hit completed response.

Example:

5

Overview

Endpoints

Upscale an image

Example: one source per mode

Example: magnific-creative with options

Credits

Errors

Authorizations

Body

Response

​Example: one source per mode

​Example: magnific-creative with options

​Credits

​Errors

Authorizations

Body

Response

Example: one source per mode

Example: magnific-creative with options

Credits

Errors