byteplus/video/upscaler

video-to-video

BytePlus Video Upscaler API by BYTEPLUS

byteplus/video/upscaler

Upscaler

BytePlus AI MediaKit video quality enhancement (super-resolution): upscale/enhance a source video to up to 8K with scene-aware models (common/ugc/short_series/aigc/old_film), optional frame-rate interpolation and color/bitrate control.

BytePlus Video Upscaler is developed by BytePlus. 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

Enhancement engine

Scene

Resolution

Resolution limit

Bitrate tier

Frame rate

Bit depth

OUTPUT

Idle

Your generated videos will appear here

Configure your settings and click Run to get started

Your request will cost $0.003 per run. For $10 you can run this model approximately 3333 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": "byteplus/video/upscaler",  # Required. model name
    "video_url": "example_value",  # Required. URL of the source video to enhance
    "tool_version": "standard",  # Enhancement engine. options: standard | professional
    "scene": "common",  # Scene template. options: common | ugc | short_series | aigc | old_film
    "resolution": "1080p",  # Target output resolution
    "resolution_limit": 128,  # Target short-edge pixel cap [128, 4320], scaled proportionally. (min: 128, max: 4320)
    "bitrate_level": "medium",  # Target bitrate tier. options: low | medium | high
    "fps": 15,  # Target frame rate [15, 120] (frame interpolation). (min: 15, max: 120)
    "bit_depth": 8,  # Color bit depth. options: 8 | 10 | 12
}

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": "byteplus/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: 9Required: 2Optional: 7

modelstringrequired

model name

Default: "byteplus/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 — BytePlus fetches the video before processing.

tool_versionstring

Enhancement engine. professional embeds 30+ algorithms for the strongest quality but costs ~10x standard.

Default: "standard"

standardprofessional

scenestring

Scene template. Only effective when tool_version=standard.

Default: "common"

commonugcshort_seriesaigcold_film

resolutionstring

Target output resolution. Mutually exclusive with resolution_limit — set only one.

Default: "1080p"

240p360p480p540p720p1080p2k4k8k

resolution_limitinteger

Target short-edge pixel cap [128, 4320], scaled proportionally. Mutually exclusive with resolution — if resolution is set, this is ignored.

Min: 128Max: 4320

bitrate_levelstring

Target bitrate tier.

Default: "medium"

lowmediumhigh

fpsinteger

Target frame rate [15, 120] (frame interpolation). Omit to keep the source frame rate. Recommended not to exceed 4x the source fps.

Min: 15Max: 120

bit_depthinteger

Color bit depth. Only effective when tool_version=professional.

Default: 8

81012

Example Request Body

{
  "model": "byteplus/video/upscaler",
  "video_url": "example_video_url",
  "tool_version": "standard",
  "scene": "common",
  "resolution": "1080p",
  "bitrate_level": "medium",
  "bit_depth": 8
}

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": "byteplus/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 — BytePlus fetches the video before processing.",
            "type": "string",
            "x-accept": "video/*",
            "x-ui-component": "uploader"
          },
          "tool_version": {
            "type": "string",
            "description": "Enhancement engine. professional embeds 30+ algorithms for the strongest quality but costs ~10x standard.",
            "default": "standard",
            "x-ui-component": "select",
            "enum": [
              "standard",
              "professional"
            ],
            "x-enum-labels": {
              "standard": "Standard — Scene-template based (fast, cost-effective)",
              "professional": "Professional — 30+ algorithms, strongest quality (~10x cost)"
            }
          },
          "scene": {
            "type": "string",
            "description": "Scene template. Only effective when tool_version=standard.",
            "default": "common",
            "x-ui-component": "select",
            "enum": [
              "common",
              "ugc",
              "short_series",
              "aigc",
              "old_film"
            ],
            "x-enum-labels": {
              "common": "Common — General-purpose enhancement",
              "ugc": "UGC — User-generated content",
              "short_series": "Short Series — Short-drama / short-series content",
              "aigc": "AIGC — AI-generated source video",
              "old_film": "Old Film — Old / degraded film restoration"
            }
          },
          "resolution": {
            "type": "string",
            "description": "Target output resolution. Mutually exclusive with resolution_limit — set only one.",
            "default": "1080p",
            "x-ui-component": "select",
            "enum": [
              "240p",
              "360p",
              "480p",
              "540p",
              "720p",
              "1080p",
              "2k",
              "4k",
              "8k"
            ],
            "x-enum-labels": {
              "240p": "240p",
              "360p": "360p",
              "480p": "480p",
              "540p": "540p",
              "720p": "720p",
              "1080p": "1080p",
              "2k": "2K",
              "4k": "4K",
              "8k": "8K"
            }
          },
          "resolution_limit": {
            "type": "integer",
            "description": "Target short-edge pixel cap [128, 4320], scaled proportionally. Mutually exclusive with resolution — if resolution is set, this is ignored.",
            "minimum": 128,
            "maximum": 4320
          },
          "bitrate_level": {
            "type": "string",
            "description": "Target bitrate tier.",
            "default": "medium",
            "x-ui-component": "select",
            "enum": [
              "low",
              "medium",
              "high"
            ],
            "x-enum-labels": {
              "low": "Low",
              "medium": "Medium",
              "high": "High"
            }
          },
          "fps": {
            "type": "integer",
            "description": "Target frame rate [15, 120] (frame interpolation). Omit to keep the source frame rate. Recommended not to exceed 4x the source fps.",
            "minimum": 15,
            "maximum": 120
          },
          "bit_depth": {
            "type": "integer",
            "description": "Color bit depth. Only effective when tool_version=professional.",
            "default": 8,
            "x-ui-component": "select",
            "enum": [
              8,
              10,
              12
            ],
            "x-enum-labels": {
              "8": "8-bit",
              "10": "10-bit",
              "12": "12-bit"
            }
          }
        },
        "required": [
          "model",
          "video_url"
        ],
        "type": "object",
        "x-order-properties": [
          "model",
          "video_url",
          "tool_version",
          "scene",
          "resolution",
          "resolution_limit",
          "bitrate_level",
          "fps",
          "bit_depth"
        ]
      },
      "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": "byteplus/video/upscaler",
  "description": "BytePlus Video Upscaler (AI MediaKit super-resolution / quality enhancement, up to 8K)"
}

LLM-Friendly Prompt Template

# byteplus/video/upscaler

> BytePlus AI MediaKit video quality enhancement (super-resolution): upscale/enhance a source video to up to 8K with scene-aware models (common/ugc/short_series/aigc/old_film), optional frame-rate interpolation and color/bitrate control.


## 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**: `byteplus/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: `"byteplus/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 — BytePlus fetches the video before processing.

- **`tool_version`** (`string`, _optional_):
  Enhancement engine. professional embeds 30+ algorithms for the strongest quality but costs ~10x standard.
  - Default: `"standard"`
  - Options: "standard", "professional"

- **`scene`** (`string`, _optional_):
  Scene template. Only effective when tool_version=standard.
  - Default: `"common"`
  - Options: "common", "ugc", "short_series", "aigc", "old_film"

- **`resolution`** (`string`, _optional_):
  Target output resolution. Mutually exclusive with resolution_limit — set only one.
  - Default: `"1080p"`
  - Options: "240p", "360p", "480p", "540p", "720p", "1080p", "2k", "4k", "8k"

- **`resolution_limit`** (`integer`, _optional_):
  Target short-edge pixel cap [128, 4320], scaled proportionally. Mutually exclusive with resolution — if resolution is set, this is ignored.
  - Min: 128
  - Max: 4320

- **`bitrate_level`** (`string`, _optional_):
  Target bitrate tier.
  - Default: `"medium"`
  - Options: "low", "medium", "high"

- **`fps`** (`integer`, _optional_):
  Target frame rate [15, 120] (frame interpolation). Omit to keep the source frame rate. Recommended not to exceed 4x the source fps.
  - Min: 15
  - Max: 120

- **`bit_depth`** (`integer`, _optional_):
  Color bit depth. Only effective when tool_version=professional.
  - Default: `8`
  - Options: 8, 10, 12



**Required Parameters Example**:

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


**Full Example**:

```json
{
  "model": "byteplus/video/upscaler",
  "video_url": "",
  "tool_version": "standard",
  "scene": "common",
  "resolution": "1080p",
  "resolution_limit": 128,
  "bitrate_level": "medium",
  "fps": 15,
  "bit_depth": 8
}
```


### 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": "byteplus/video/upscaler",
  "video_url": "",
  "tool_version": "standard",
  "scene": "common",
  "resolution": "1080p",
  "resolution_limit": 128,
  "bitrate_level": "medium",
  "fps": 15,
  "bit_depth": 8
}'

# 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/byteplus/video/upscaler)

BytePlus Video Upscaler

BytePlus Video Upscaler enhances an existing video to a higher output resolution and better quality using BytePlus AI MediaKit super-resolution. Provide a public video URL, pick the engine and target resolution, and receive a playable enhanced video URL.

Highlights

Video-to-video enhancement: Improve an existing clip (up to 8K) without changing the source content.
Scene-aware standard engine: standard uses a scene template — common, ugc, short_series, aigc (AI-generated source), or old_film (degraded footage) — for fast, cost-effective results.
Professional engine: professional runs 30+ algorithms for the strongest quality (higher latency and ~10x the cost of standard).
Flexible output control: Target a fixed resolution (240p–8k) or a short-edge pixel cap, tune the bitrate tier, and optionally interpolate the frame rate.
Hosted output: Enhanced videos are transferred to AtlasCloud storage and returned as long-lived URLs (the upstream URL expires in 24 hours and is never exposed).

Parameters

Parameter	Required	Description
`model`	Yes	Use `byteplus/video/upscaler`.
`video_url`	Yes	Input video URL. Must be a publicly accessible HTTP(S) URL — BytePlus fetches it before processing, so signed URLs should be long-lived.
`tool_version`	No	Engine: `standard` (default) or `professional` (~10x cost).
`scene`	No	Scene template, only effective when `tool_version=standard`: `common` (default), `ugc`, `short_series`, `aigc`, `old_film`.
`resolution`	No	Target output resolution: `240p`, `360p`, `480p`, `540p`, `720p`, `1080p` (default), `2k`, `4k`, `8k`. Mutually exclusive with `resolution_limit`.
`resolution_limit`	No	Target short-edge pixel cap `[128, 4320]`, scaled proportionally. Mutually exclusive with `resolution` — if `resolution` is set, this is ignored.
`bitrate_level`	No	Target bitrate tier: `low`, `medium` (default), `high`.
`fps`	No	Target frame rate `[15, 120]` (frame interpolation). Omit to keep the source frame rate. Recommended not to exceed 4x the source fps.
`bit_depth`	No	Color bit depth: `8` (default), `10`, `12`. Only effective when `tool_version=professional`.

Note: resolution and resolution_limit cannot be set at the same time. If both are provided, resolution takes precedence and resolution_limit is dropped.

Example Request

{
  "model": "byteplus/video/upscaler",
  "video_url": "https://static.atlascloud.ai/media/videos/af3ce4416487e61f8b299c5dc42642e3.mp4",
  "tool_version": "standard",
  "scene": "aigc",
  "resolution": "1080p"
}

Processing

Enhancement is asynchronous. Submit a request to receive a task id, then poll the result endpoint until status is completed (or failed). A standard-engine 1-minute video typically takes about 6–10 minutes.

Pricing

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

price = duration_seconds × $0.00344333 × resolution_factor × fps_factor × version_factor

Base rate: $0.00344333 / second (equivalent to $0.2066 / minute).
Resolution factor: 720p and below = 1, 1080p = 2, 2K = 4, 4K = 8, 8K = 32.
Frame-rate factor: ≤30fps = 1, >30 and ≤60fps = 2, >60 and ≤120fps = 4.
Version factor: standard = 1, professional = 10.

When fps is omitted (source frame rate preserved) it is billed at the ≤60fps tier (factor 2); when resolution is omitted it is billed at the 1080p tier (factor 2).

Effective per-minute price (base × factors):

Resolution	≤30fps	≤60fps	≤120fps
720p / below	`$0.2066`	`$0.4132`	`$0.8264`
1080p	`$0.4132`	`$0.8264`	`$1.6528`
2K	`$0.8264`	`$1.6528`	`$3.3056`
4K	`$1.6528`	`$3.3056`	`$6.6112`
8K	`$6.6112`	`$13.2224`	`$26.4448`

professional multiplies every cell above by 10.

Example: a 11-second professional job at 2K and 56fps → 11 × $0.00344333 × 4 × 2 × 10 = $3.03.

BytePlus Video Upscaler API by BYTEPLUS

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

BytePlus Video Upscaler

Highlights

Parameters

Example Request

Processing

Pricing

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One API for All Media AI.

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