tencent/video/upscaler

video-to-video

Tencent Video Upscaler API by TENCENT

tencent/video/upscaler

Upscaler

Tencent Video Upscaler (MPS super-resolution / enhancement)

Tencent Video Upscaler is developed by Tencent. Atlas Cloud (operated by Atlas Cloud AI LLC) provides access to it and does not own it. All trademarks belong to their respective owners.

INPUT

Video *

You can drag and drop a file or click to upload

MAX:1

Template

Short edge

Frame rate

Keep metadata

OUTPUT

Idle

Your generated videos will appear here

Configure your settings and click Run to get started

Your request will cost $0.004 per run. For $10 you can run this model approximately 2500 times.

Here's what you can do next:

Seedance 2.0 Kling v3 Vidu Wan2.7

Parameters

Code Example
import requests
import time

# Step 1: Start video generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "tencent/video/upscaler",  # Required. model name
    "video_url": "example_value",  # Required. URL of the source video to enhance
    "template": "anime-enhance-4k",  # Enhancement template
    "short": 0,  # Output short-edge in pixels. (min: 0, max: 2160)
    "fps": 1,  # Smart frame-interpolation target FPS. (min: 1)
    "keep_metadata": True,  # Whether to preserve the source media metadata
}

generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]

# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"

def check_status():
    while True:
        response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
        result = response.json()

        if result["data"]["status"] in ["completed", "succeeded"]:
            print("Generated video:", result["data"]["outputs"][0])
            return result["data"]["outputs"][0]
        elif result["data"]["status"] == "failed":
            raise Exception(result["data"]["error"] or "Generation failed")
        else:
            # Still processing, wait 2 seconds
            time.sleep(2)

video_url = check_status()

Install

Install the required package for your language.

pip install requests

Authentication

All API requests require authentication via an API key. You can get your API key from the Atlas Cloud dashboard.

export ATLASCLOUD_API_KEY="your-api-key-here"

HTTP Headers

import os

API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {API_KEY}"
}

Keep your API key secure

Never expose your API key in client-side code or public repositories. Use environment variables or a backend proxy instead.

Submit a request

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "your-model",
    "prompt": "A beautiful landscape"
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

Submit a Request

Submit an asynchronous generation request. The API returns a prediction ID that you can use to check the status and retrieve the result.

POST/api/v1/model/generateVideo

Request Body

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}

data = {
    "model": "tencent/video/upscaler",
    "prompt": "A beautiful sunset over the ocean with gentle waves"
}

response = requests.post(url, headers=headers, json=data)
result = response.json()

print(f"Prediction ID: {result['data']['id']}")
print(f"Status: {result['data']['status']}")

Response

{
  "code": 200,
  "data": {
    "id": "pred_abc123",
    "status": "processing",
    "model": "model-name",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

Check Status

Poll the prediction endpoint to check the current status of your request.

GET/api/v1/model/prediction/{prediction_id}

Polling Example

import requests
import time

prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

while True:
    response = requests.get(url, headers=headers)
    result = response.json()
    status = result["data"]["status"]
    print(f"Status: {status}")

    if status in ["completed", "succeeded"]:
        output_url = result["data"]["outputs"][0]
        print(f"Output URL: {output_url}")
        break
    elif status == "failed":
        print(f"Error: {result['data'].get('error', 'Unknown')}")
        break

    time.sleep(3)

Status Values

processingThe request is still being processed.

completedGeneration is complete. Outputs are available.

succeededGeneration succeeded. Outputs are available.

failedGeneration failed. Check the error field.

Completed Response

{
  "data": {
    "id": "pred_abc123",
    "status": "completed",
    "outputs": [
      "https://storage.atlascloud.ai/outputs/result.mp4"
    ],
    "metrics": {
      "predict_time": 45.2
    },
    "created_at": "2025-01-01T00:00:00Z",
    "completed_at": "2025-01-01T00:00:10Z"
  }
}

Upload Files

Upload files to Atlas Cloud storage and get a URL you can use in your API requests. Use multipart/form-data to upload.

POST/api/v1/model/uploadMedia

Upload Example

import requests

url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

with open("image.png", "rb") as f:
    files = {"file": ("image.png", f, "image/png")}
    response = requests.post(url, headers=headers, files=files)

result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}")

Response

{
  "data": {
    "download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
    "file_name": "image.png",
    "content_type": "image/png",
    "size": 1024000
  }
}

Input Schema

The following parameters are accepted in the request body.

Total: 6Required: 2Optional: 4

modelstringrequired

model name

Default: "tencent/video/upscaler"

video_urlstringrequired

URL of the source video to enhance. Must be a publicly accessible HTTP(S) URL (user-uploaded or third-party-model output are both supported). Signed URLs should be long-lived — Tencent MPS fetches the video before processing.

templatestring

Enhancement template. The frontend shows the label; the backend maps the slug to the corresponding MPS template ID (Definition).

Default: "anime-enhance-4k"

live-action-enhance-720plive-action-enhance-1080plive-action-enhance-2klive-action-enhance-4kanime-enhance-720panime-enhance-1080panime-enhance-2kanime-enhance-4krestore-720prestore-1080prestore-2krestore-4klive-action-smallface-720plive-action-smallface-1080plive-action-smallface-2klive-action-smallface-4kanime-smallface-720panime-smallface-1080panime-smallface-2kanime-smallface-4kseedance2-enhance-720pseedance2-enhance-1080pseedance2-enhance-2kseedance2-enhance-4k

shortinteger

Output short-edge in pixels. Range is constrained by the chosen template tier (see x-depends-on). Special value 0 = keep source resolution.

Default: 0Min: 0Max: 2160

fpsinteger

Smart frame-interpolation target FPS. Omit to keep source frame rate.

Min: 1

keep_metadataboolean

Whether to preserve the source media metadata.

Default: true

Example Request Body

{
  "model": "tencent/video/upscaler",
  "video_url": "example_video_url",
  "template": "anime-enhance-4k",
  "short": 0,
  "keep_metadata": true
}

Output Schema

The API returns a prediction response with the generated output URLs.

created_atstring

ISO timestamp of when the request was created.

idstring

Unique identifier for the prediction.

modelstring

Model ID used for the prediction.

outputsarray

Array of URLs to the enhanced video(s).

statusstring

Status of the task: created, processing, completed, or failed.

Example Response

{
  "id": "pred_abc123",
  "status": "completed",
  "model": "model-name",
  "outputs": [
    "https://storage.atlascloud.ai/outputs/result.mp4"
  ],
  "metrics": {
    "predict_time": 45.2
  },
  "created_at": "2025-01-01T00:00:00Z",
  "completed_at": "2025-01-01T00:00:10Z"
}

Atlas Cloud Skills

Atlas Cloud Skills integrates 400+ AI models directly into your AI coding assistant. One command to install, then use natural language to generate images, videos, and chat with LLMs.

Supported Clients

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ supported clients

Install

npx skills add AtlasCloudAI/atlas-cloud-skills

Setup API Key

Get your API key from the Atlas Cloud dashboard and set it as an environment variable.

export ATLASCLOUD_API_KEY="your-api-key-here"

Capabilities

Once installed, you can use natural language in your AI assistant to access all Atlas Cloud models.

Image GenerationGenerate images with models like Nano Banana 2, Z-Image, and more.

Video CreationCreate videos from text or images with Kling, Vidu, Veo, etc.

LLM ChatChat with Qwen, DeepSeek, and other large language models.

Media UploadUpload local files for image editing and image-to-video workflows.

Learn more

github.com/AtlasCloudAI/atlas-cloud-skills

MCP Server

Atlas Cloud MCP Server connects your IDE with 400+ AI models via the Model Context Protocol. Works with any MCP-compatible client.

Supported Clients

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ supported clients

Install

npx -y atlascloud-mcp

Configuration

Add the following configuration to your IDE's MCP settings file.

{
  "mcpServers": {
    "atlascloud": {
      "command": "npx",
      "args": [
        "-y",
        "atlascloud-mcp"
      ],
      "env": {
        "ATLASCLOUD_API_KEY": "your-api-key-here"
      }
    }
  }
}

Available Tools

atlas_generate_imageGenerate images from text prompts.

atlas_generate_videoCreate videos from text or images.

atlas_chatChat with large language models.

atlas_list_modelsBrowse 400+ available AI models.

atlas_quick_generateOne-step content creation with auto model selection.

atlas_upload_mediaUpload local files for API workflows.

Learn more

github.com/AtlasCloudAI/mcp-server

API Schema

{
  "components": {
    "schemas": {
      "Input": {
        "properties": {
          "model": {
            "type": "string",
            "description": "model name",
            "default": "tencent/video/upscaler"
          },
          "video_url": {
            "description": "URL of the source video to enhance. Must be a publicly accessible HTTP(S) URL (user-uploaded or third-party-model output are both supported). Signed URLs should be long-lived — Tencent MPS fetches the video before processing.",
            "type": "string",
            "x-accept": "video/*",
            "x-ui-component": "uploader"
          },
          "template": {
            "type": "string",
            "description": "Enhancement template. The frontend shows the label; the backend maps the slug to the corresponding MPS template ID (Definition).",
            "default": "anime-enhance-4k",
            "x-ui-component": "select",
            "enum": [
              "live-action-enhance-720p",
              "live-action-enhance-1080p",
              "live-action-enhance-2k",
              "live-action-enhance-4k",
              "anime-enhance-720p",
              "anime-enhance-1080p",
              "anime-enhance-2k",
              "anime-enhance-4k",
              "restore-720p",
              "restore-1080p",
              "restore-2k",
              "restore-4k",
              "live-action-smallface-720p",
              "live-action-smallface-1080p",
              "live-action-smallface-2k",
              "live-action-smallface-4k",
              "anime-smallface-720p",
              "anime-smallface-1080p",
              "anime-smallface-2k",
              "anime-smallface-4k",
              "seedance2-enhance-720p",
              "seedance2-enhance-1080p",
              "seedance2-enhance-2k",
              "seedance2-enhance-4k"
            ],
            "x-enum-labels": {
              "live-action-enhance-720p": "Live-action · AI Enhance · 720P",
              "live-action-enhance-1080p": "Live-action · AI Enhance · 1080P",
              "live-action-enhance-2k": "Live-action · AI Enhance · 2K",
              "live-action-enhance-4k": "Live-action · AI Enhance · 4K",
              "anime-enhance-720p": "Anime/Comic · AI Enhance · 720P",
              "anime-enhance-1080p": "Anime/Comic · AI Enhance · 1080P",
              "anime-enhance-2k": "Anime/Comic · AI Enhance · 2K",
              "anime-enhance-4k": "Anime/Comic · AI Enhance · 4K",
              "restore-720p": "Old/Low-quality Restore · 720P",
              "restore-1080p": "Old/Low-quality Restore · 1080P",
              "restore-2k": "Old/Low-quality Restore · 2K",
              "restore-4k": "Old/Low-quality Restore · 4K",
              "live-action-smallface-720p": "Live-action · Small-face Optimize · 720P",
              "live-action-smallface-1080p": "Live-action · Small-face Optimize · 1080P",
              "live-action-smallface-2k": "Live-action · Small-face Optimize · 2K",
              "live-action-smallface-4k": "Live-action · Small-face Optimize · 4K",
              "anime-smallface-720p": "Anime/Comic · Small-face Optimize · 720P",
              "anime-smallface-1080p": "Anime/Comic · Small-face Optimize · 1080P",
              "anime-smallface-2k": "Anime/Comic · Small-face Optimize · 2K",
              "anime-smallface-4k": "Anime/Comic · Small-face Optimize · 4K",
              "seedance2-enhance-720p": "Seedance2 Enhance · 720P",
              "seedance2-enhance-1080p": "Seedance2 Enhance · 1080P",
              "seedance2-enhance-2k": "Seedance2 Enhance · 2K",
              "seedance2-enhance-4k": "Seedance2 Enhance · 4K"
            }
          },
          "short": {
            "type": "integer",
            "description": "Output short-edge in pixels. Range is constrained by the chosen template tier (see x-depends-on). Special value 0 = keep source resolution.",
            "default": 0,
            "minimum": 0,
            "maximum": 2160,
            "x-depends-on": {
              "field": "template",
              "conditions": [
                {
                  "when": [
                    "live-action-enhance-720p",
                    "anime-enhance-720p",
                    "restore-720p",
                    "live-action-smallface-720p",
                    "anime-smallface-720p",
                    "seedance2-enhance-720p"
                  ],
                  "minimum": 0,
                  "maximum": 720,
                  "description": "720P templates: 0 (keep source) or 1–720"
                },
                {
                  "when": [
                    "live-action-enhance-1080p",
                    "anime-enhance-1080p",
                    "restore-1080p",
                    "live-action-smallface-1080p",
                    "anime-smallface-1080p",
                    "seedance2-enhance-1080p"
                  ],
                  "minimum": 721,
                  "maximum": 1080,
                  "description": "1080P templates: 721–1080"
                },
                {
                  "when": [
                    "live-action-enhance-2k",
                    "anime-enhance-2k",
                    "restore-2k",
                    "live-action-smallface-2k",
                    "anime-smallface-2k",
                    "seedance2-enhance-2k"
                  ],
                  "minimum": 1081,
                  "maximum": 1440,
                  "description": "2K templates: 1081–1440"
                },
                {
                  "when": [
                    "live-action-enhance-4k",
                    "anime-enhance-4k",
                    "restore-4k",
                    "live-action-smallface-4k",
                    "anime-smallface-4k",
                    "seedance2-enhance-4k"
                  ],
                  "minimum": 1441,
                  "maximum": 2160,
                  "description": "4K templates: 1441–2160"
                }
              ]
            }
          },
          "fps": {
            "type": "integer",
            "description": "Smart frame-interpolation target FPS. Omit to keep source frame rate.",
            "minimum": 1
          },
          "keep_metadata": {
            "type": "boolean",
            "description": "Whether to preserve the source media metadata.",
            "default": true
          }
        },
        "required": [
          "model",
          "video_url"
        ],
        "type": "object",
        "x-order-properties": [
          "model",
          "video_url",
          "template",
          "short",
          "fps",
          "keep_metadata"
        ]
      },
      "PredictionResponse": {
        "properties": {
          "created_at": {
            "description": "ISO timestamp of when the request was created.",
            "format": "date-time",
            "type": "string"
          },
          "id": {
            "description": "Unique identifier for the prediction.",
            "type": "string"
          },
          "model": {
            "description": "Model ID used for the prediction.",
            "type": "string"
          },
          "outputs": {
            "description": "Array of URLs to the enhanced video(s).",
            "items": {
              "type": "string"
            },
            "type": "array"
          },
          "status": {
            "description": "Status of the task: created, processing, completed, or failed.",
            "type": "string"
          },
          "urls": {
            "description": "Object containing related API endpoints.",
            "type": "object"
          }
        },
        "type": "object"
      }
    },
    "securitySchemes": {
      "apiKeyAuth": {
        "in": "header",
        "name": "Authorization",
        "type": "apiKey"
      }
    }
  },
  "info": {
    "description": "The AtlasCloud API.",
    "title": "AtlasCloud API",
    "version": "1.0.0"
  },
  "openapi": "3.0.0",
  "paths": {
    "/api/v1/model/generateVideo": {
      "post": {
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/Input"
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "The request status."
          }
        }
      },
      "x-api-name": "model_run"
    },
    "/api/v1/model/result/{request_id}": {
      "get": {
        "parameters": [
          {
            "in": "path",
            "name": "request_id",
            "required": true,
            "schema": {
              "description": "Request ID",
              "type": "string"
            }
          }
        ],
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "Result of the request."
          }
        }
      },
      "x-api-name": "model_result"
    }
  },
  "servers": [
    {
      "url": "https://api.atlascloud.ai"
    }
  ],
  "model": "tencent/video/upscaler",
  "description": "Tencent Video Upscaler 4K (MPS super-resolution / enhancement)"
}

LLM-Friendly Prompt Template

# tencent/video/upscaler

> Tencent Video Upscaler (MPS super-resolution / enhancement)


## Overview

- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateVideo` — start an async generation; returns a `prediction_id`
- **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes
- **Model ID**: `tencent/video/upscaler`


## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:

- **`model`** (`string`, _required_):
  model name
  - Default: `"tencent/video/upscaler"`

- **`video_url`** (`string`, _required_):
  URL of the source video to enhance. Must be a publicly accessible HTTP(S) URL (user-uploaded or third-party-model output are both supported). Signed URLs should be long-lived — Tencent MPS fetches the video before processing.

- **`template`** (`string`, _optional_):
  Enhancement template. The frontend shows the label; the backend maps the slug to the corresponding MPS template ID (Definition).
  - Default: `"anime-enhance-4k"`
  - Options: "live-action-enhance-720p", "live-action-enhance-1080p", "live-action-enhance-2k", "live-action-enhance-4k", "anime-enhance-720p", "anime-enhance-1080p", "anime-enhance-2k", "anime-enhance-4k", "restore-720p", "restore-1080p", "restore-2k", "restore-4k", "live-action-smallface-720p", "live-action-smallface-1080p", "live-action-smallface-2k", "live-action-smallface-4k", "anime-smallface-720p", "anime-smallface-1080p", "anime-smallface-2k", "anime-smallface-4k", "seedance2-enhance-720p", "seedance2-enhance-1080p", "seedance2-enhance-2k", "seedance2-enhance-4k"

- **`short`** (`integer`, _optional_):
  Output short-edge in pixels. Range is constrained by the chosen template tier (see x-depends-on). Special value 0 = keep source resolution.
  - Default: `0`
  - Min: 0
  - Max: 2160

- **`fps`** (`integer`, _optional_):
  Smart frame-interpolation target FPS. Omit to keep source frame rate.
  - Min: 1

- **`keep_metadata`** (`boolean`, _optional_):
  Whether to preserve the source media metadata.
  - Default: `true`



**Required Parameters Example**:

```json
{
  "model": "tencent/video/upscaler",
  "video_url": ""
}
```


**Full Example**:

```json
{
  "model": "tencent/video/upscaler",
  "video_url": "",
  "template": "anime-enhance-4k",
  "short": 0,
  "fps": 1,
  "keep_metadata": true
}
```


### Output Schema

The API returns the following output format:


- **`created_at`** (`string`, _optional_):
  ISO timestamp of when the request was created.

- **`id`** (`string`, _optional_):
  Unique identifier for the prediction.

- **`model`** (`string`, _optional_):
  Model ID used for the prediction.

- **`outputs`** (`array[string]`, _optional_):
  Array of URLs to the enhanced video(s).

- **`status`** (`string`, _optional_):
  Status of the task: created, processing, completed, or failed.

- **`urls`** (`object`, _optional_):
  Object containing related API endpoints.



**Example Response**:

```json
{
  "created_at": "",
  "id": "",
  "model": "",
  "outputs": [
    ""
  ],
  "status": "",
  "urls": {}
}
```


## Usage Examples

### cURL

```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateVideo" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "tencent/video/upscaler",
  "video_url": "",
  "template": "anime-enhance-4k",
  "short": 0,
  "fps": 1,
  "keep_metadata": true
}'

# Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}}

# Step 2: Poll for result (replace {prediction_id} with the id returned above)
curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY"

# Keep polling until status is "completed", "succeeded" or "failed"
# When completed, outputs will contain the generated content URL(s)
```

## Additional Resources

### Documentation

- [Model Playground](https://www.atlascloud.ai/models/tencent/video/upscaler)

Tencent Video Upscaler

Tencent Video Upscaler enhances an existing video to a higher output resolution and better quality using Tencent Cloud MPS (Media Processing Service) large-model super-resolution. Provide a public video URL, pick an enhancement template, and receive a playable enhanced video URL.

Highlights

Video-to-video enhancement: Improve an existing clip (up to 4K) without changing the source content. User-uploaded videos and third-party-model outputs are both supported.
Scene-tuned templates: Choose a template matched to your content and target resolution — live-action / anime-comic AI enhance, old-film & low-quality restoration (denoise + face enhance + descratch), distant small-face optimization, or Seedance2-tuned enhancement — at 720P / 1080P / 2K / 4K.
Optional fine control: Override the output short-edge and interpolate the frame rate when needed; otherwise the template's tier and the source frame rate are used.
Hosted output: Enhanced videos are transferred to AtlasCloud storage and returned as long-lived URLs (the upstream Tencent COS URL is never exposed).

Parameters

Parameter	Required	Description
`model`	Yes	Use `tencent/video/upscaler`.
`video_url`	Yes	Input video URL. Must be a publicly accessible HTTP(S) URL — Tencent MPS fetches it before processing, so signed URLs should be long-lived.
`template`	Yes	Enhancement template. Selects the scene and target resolution tier (see the table below). Default `anime-enhance-4k`.
`short`	No	Output short-edge in pixels, constrained by the chosen template tier: 720P `(0,720]`, 1080P `(720,1080]`, 2K `(1080,1440]`, 4K `(1440,2160]`. Omit to use the template's default output size. Does not affect billing.
`fps`	No	Target frame rate (frame interpolation). Omit to keep the source frame rate.
`keep_metadata`	No	Whether to preserve the source media metadata. Default `true`.

`template` options

Slug	Scene / Effect	Tiers
`live-action-enhance-{720p,1080p,2k,4k}`	Live-action · AI Enhance	720P–4K
`anime-enhance-{720p,1080p,2k,4k}`	Anime/Comic · AI Enhance	720P–4K
`restore-{720p,1080p,2k,4k}`	Old/Low-quality Restore (denoise + face enhance + descratch)	720P–4K
`live-action-smallface-{720p,1080p,2k,4k}`	Live-action · Small-face Optimize	720P–4K
`anime-smallface-{720p,1080p,2k,4k}`	Anime/Comic · Small-face Optimize	720P–4K
`seedance2-enhance-{720p,1080p,2k,4k}`	Seedance2-tuned Enhance	720P–4K

Note: The template you choose determines both the enhancement behavior and the billing tier. short is an optional output-size override and must stay within the chosen template's tier range.

Processing

Enhancement is asynchronous. Submit a request to receive a task id, then poll the result endpoint until status is completed (or failed). Enhanced output is transferred to AtlasCloud storage and returned in outputs as a long-lived URL.

Pricing

Billing is per second of video duration (probed server-side via ffprobe before billing). The final price is the duration multiplied by a per-second rate determined by the template's resolution tier and a frame-rate coefficient:

price = duration_seconds × tier_rate × fps_factor

Resolution tier is taken from the template (its trailing 720p / 1080p / 2k / 4k), not from short.
Per-second tier rate (equivalent per-minute rate in parentheses):

Tier Per second (Per minute)
720P $0.004110 $0.2466
1080P $0.009092 $0.5455
2K $0.016507 $0.9904
4K $0.036542 $2.1925
Frame-rate factor: ≤30fps = 1, >30 and ≤60fps = 2, >60 and ≤120fps = 4. When fps is omitted it is billed at the ≤30fps tier (factor 1).

Effective per-minute price (tier rate × fps factor):

Tier	≤30fps	≤60fps	≤120fps
720P	`$0.2466`	`$0.4932`	`$0.9864`
1080P	`$0.5455`	`$1.0910`	`$2.1820`
2K	`$0.9904`	`$1.9808`	`$3.9616`
4K	`$2.1925`	`$4.3850`	`$8.7700`

Example: a 30-second anime-enhance-2k job at the default ≤30fps → 30 × $0.016507 × 1 = $0.4952.

Tier	Per second	(Per minute)
720P	`$0.004110`	`$0.2466`
1080P	`$0.009092`	`$0.5455`
2K	`$0.016507`	`$0.9904`
4K	`$0.036542`	`$2.1925`

Tencent Video Upscaler API by TENCENT

INPUT

OUTPUT

Parameters

Code Example

Install

Authentication

HTTP Headers

Submit a request

Submit a Request

Request Body

Response

Check Status

Polling Example

Status Values

Completed Response

Upload Files

Upload Example

Response

Input Schema

Example Request Body

Output Schema

Example Response

Atlas Cloud Skills

Supported Clients

Install

Setup API Key

Capabilities

MCP Server

Supported Clients

Install

Configuration

Available Tools

API Schema

LLM-Friendly Prompt Template

Tencent Video Upscaler

Highlights

Parameters

template options

Processing

Pricing

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INPUT

OUTPUT

Parameters

Code Example

Install

Authentication

HTTP Headers

Submit a request

Submit a Request

Request Body

Response

Check Status

Polling Example

Status Values

Completed Response

Upload Files

Upload Example

Response

Input Schema

Example Request Body

Output Schema

`template` options