Video Upscaling Guide | Venice API Docs

Video upscaling lets you enhance existing videos to higher resolutions while improving visual quality. The Topaz Video Upscale model uses AI-powered upscaling to increase resolution by 2x or 4x, or apply quality enhancement at the original resolution (1x).

How it works

Video upscaling uses the same async queue system as video generation:

Queue — Submit your video to /video/queue with the topaz-video-upscale model
Poll — Check /video/retrieve with the returned queue_id until the status is completed
Complete — Call /video/complete to finalize and get the output URL

The server automatically detects the input video’s duration, frame rate, and dimensions from the uploaded file. You don’t need to provide these values — billing is calculated from the actual video metadata.

Upscale factors

`upscale_factor`	Output resolution	Use case
`1`	Same as input	Quality enhancement only (denoising, sharpening)
`2` (default)	2x input dimensions	Standard upscale — 720p input becomes 1440p output
`4`	4x input dimensions	Maximum upscale — 480p input becomes 1920p output

The upscale_factor parameter replaces resolution for upscale models. Passing resolution will return an error. This is because the output resolution depends on the input video’s dimensions — a 2x upscale of a 720p video produces a different result than a 2x upscale of a 480p video.

Supported input formats

Formats: MP4, MOV, WebM
Input methods: HTTPS URL or data:video/...;base64,... data URL
Max duration: 300 seconds (5 minutes)

API usage

Queue an upscale job

curl https://api.venice.ai/api/v1/video/queue \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "topaz-video-upscale",
    "video_url": "https://example.com/input-video.mp4",
    "upscale_factor": 2
  }'

import requests

response = requests.post(
    "https://api.venice.ai/api/v1/video/queue",
    headers={"Authorization": "Bearer YOUR_API_KEY"},
    json={
        "model": "topaz-video-upscale",
        "video_url": "https://example.com/input-video.mp4",
        "upscale_factor": 2,
    },
)

data = response.json()
queue_id = data["queue_id"]
print(f"Queued: {queue_id}")

const response = await fetch("https://api.venice.ai/api/v1/video/queue", {
  method: "POST",
  headers: {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    model: "topaz-video-upscale",
    video_url: "https://example.com/input-video.mp4",
    upscale_factor: 2,
  }),
});

const { queue_id } = await response.json();
console.log(`Queued: ${queue_id}`);

The response includes a queue_id to track the job:

{
  "model": "topaz-video-upscale",
  "queue_id": "abc123-def456-..."
}

Poll for completion

curl https://api.venice.ai/api/v1/video/retrieve \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"queue_id": "abc123-def456-..."}'

import time

while True:
    result = requests.post(
        "https://api.venice.ai/api/v1/video/retrieve",
        headers={"Authorization": "Bearer YOUR_API_KEY"},
        json={"queue_id": queue_id},
    )
    data = result.json()

    if data.get("status") == "completed":
        print(f"Video URL: {data['url']}")
        break

    time.sleep(5)

const poll = async (queueId) => {
  while (true) {
    const res = await fetch("https://api.venice.ai/api/v1/video/retrieve", {
      method: "POST",
      headers: {
        "Authorization": "Bearer YOUR_API_KEY",
        "Content-Type": "application/json",
      },
      body: JSON.stringify({ queue_id: queueId }),
    });
    const data = await res.json();

    if (data.status === "completed") {
      console.log(`Video URL: ${data.url}`);
      return data;
    }

    await new Promise((r) => setTimeout(r, 5000));
  }
};

await poll(queue_id);

Finalize with complete

After retrieving the result, call /video/complete to finalize:

curl https://api.venice.ai/api/v1/video/complete \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"queue_id": "abc123-def456-..."}'

API parameters

Field	Type	Required	Description
`model`	string	Yes	Must be `topaz-video-upscale`
`video_url`	string	Yes	Input video URL or data URL. Supported formats: MP4, MOV, WebM.
`upscale_factor`	number	No	`1`, `2` (default), or `4`. Controls the upscale multiplier.

Parameters not used for upscale models

The following parameters are not accepted for topaz-video-upscale and will return an error if provided:

Field	Reason
`resolution`	Use `upscale_factor` instead. Output resolution depends on input dimensions.
`prompt`	Upscaling does not use text prompts. An empty string is set automatically.

The duration parameter is also ignored — the server detects duration directly from the video file for billing accuracy.

Pricing

Pricing is based on duration, output resolution tier, and frame rate. The output resolution tier is determined by the input video’s height multiplied by the upscale factor.

Output resolution tiers

Tier	Output height	Per-second rate
720p	≤ 720px	~$0.013
1080p	721–1080px	~$0.025
4K	> 1080px	~$0.10

Videos with frame rates above 48fps cost 2x the per-second rate.

Pricing examples

Input	Upscale factor	Output	Duration	Estimated cost
480p, 30fps	2x	960p (1080p tier)	10s	~$0.25
720p, 30fps	2x	1440p (4K tier)	10s	~$1.00
1080p, 30fps	2x	2160p (4K tier)	30s	~$3.00
360p, 24fps	4x	1440p (4K tier)	10s	~$1.00
480p, 60fps	2x	960p (1080p tier)	10s	~$0.50

Use the Video Quote API to get exact pricing before submitting a job.

Getting a quote

curl https://api.venice.ai/api/v1/video/quote \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "topaz-video-upscale",
    "duration": "10",
    "input_height": 720
  }'

The quote endpoint accepts input_height so it can estimate the output resolution tier. This is optional — if omitted, the quote assumes a conservative estimate.

Troubleshooting

Problem	Likely cause	Fix
`"Use upscale_factor instead of resolution"`	`resolution` was passed in the request	Remove `resolution` and use `upscale_factor` instead
Higher-than-expected cost	Input video has high resolution or high FPS	Check input dimensions with the quote endpoint. 720p+ input with 2x upscale lands in the 4K pricing tier.
Job takes a long time	Large or long video	Upscaling is compute-intensive. Longer videos and higher upscale factors take proportionally longer.
`"Insufficient balance"`	Account credits too low	Add credits at venice.ai/settings/api

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Agent Tooling

SDKs & Frameworks

Video Upscaling

How it works

Upscale factors

Supported input formats

API usage

Queue an upscale job

Poll for completion

Finalize with complete

API parameters

Parameters not used for upscale models

Pricing

Output resolution tiers

Pricing examples

Getting a quote

Troubleshooting

​How it works

​Upscale factors

​Supported input formats

​API usage

​Queue an upscale job

​Poll for completion

​Finalize with complete

​API parameters

​Parameters not used for upscale models

​Pricing

​Output resolution tiers

​Pricing examples

​Getting a quote

​Troubleshooting

How it works

Upscale factors

Supported input formats

API usage

Queue an upscale job

Poll for completion

Finalize with complete

API parameters

Parameters not used for upscale models

Pricing

Output resolution tiers

Pricing examples

Getting a quote

Troubleshooting