Topaz · Utility

OpenClaw x Topaz

Topaz Labs specializes in AI media enhancement with dedicated image and video upscaling models. Through RunAPI, both upscale endpoints share unified billing.

2 variants from $0.14 / second Commercial OK
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Prerequisite: npx runapi mcp install

Prompt

Prompt models

Use topaz-upscale-image when it matches the task: Neural image upscaling; recovers detail without artifacts.

You have access to RunAPI task tools for Topaz.

Available Topaz models:
- topaz-upscale-image: Neural image upscaling; recovers detail without artifacts
  endpoints: /api/v1/topaz/upscale_image
  request fields: model, source_image_url, upscale_factor
- topaz-upscale-video: Frame-by-frame video upscaling with temporal consistency
  endpoints: /api/v1/topaz/upscale_video
  request fields: model, source_video_url

Use the model ID and endpoint that match the user's request.
Example prompt: Upscale this 720p product photo to 4K while preserving fine texture detail and removing noise.
/api/v1/topaz/upscale_image: Submit the task, poll for its status, then verify the completed output. POST /api/v1/topaz/upscale_image and save the returned Task id.
GET /api/v1/topaz/upscale_image/<task-id> until status is completed or failed.
Verify the completed response contains the endpoint-specific output documented in the API reference.
/api/v1/topaz/upscale_video: Submit the task, poll for its status, then verify the completed output. POST /api/v1/topaz/upscale_video and save the returned Task id.
GET /api/v1/topaz/upscale_video/<task-id> until status is completed or failed.
Verify the completed response contains the endpoint-specific output documented in the API reference.

Public Versions and Endpoints

Model ID Endpoints Price Catalog
topaz-upscale-image
/api/v1/topaz/upscale_image
$0.20 / call Model detail
topaz-upscale-video
/api/v1/topaz/upscale_video
$0.14 / second Model detail

Verify

Poll until the task reaches a terminal status

Select <model-id> to generate verification commands.

Configuration

Guide endpoint: <endpoint>

Select <model-id> to generate a request with the endpoint's public input contract.
How it works

Get Started in 3 Steps

  1. Choose a model ID

    Select a public catalog model ID and review its endpoint and current starting price.

  2. Configure RunAPI

    Set RUNAPI_API_KEY before making the endpoint request.

  3. Verify the result

    For asynchronous endpoints, poll the same endpoint until the Task reaches a terminal status.

What to Build with OpenClaw + Topaz

  • Upscaling AI-generated images for print

    Take outputs from any generation model and upscale them for large-format posters, packaging, or other print work.

  • Noise reduction and face restoration

    Clean up noisy low-light photos and restore blurry faces, recovering detail lost to compression or poor capture conditions.

  • Batch processing large photo collections

    Run hundreds of product photos or archival images through upscaling in one pipeline, with each image handled as its own task.

Why Use Topaz Through RunAPI + OpenClaw

  • 2 variants, one API key

    Use one RunAPI connection to choose among the live model variants without changing your integration.

  • Clear usage pricing

    See current catalog pricing before you send a request, with no subscription or minimum spend required.

  • Automatic task workflows

    Submit, poll, and collect asynchronous results through a consistent task workflow without writing manual polling code.

OpenClaw + Topaz Questions

Can I use Topaz in OpenClaw?

Yes. Configure RunAPI as a provider in OpenClaw, then ask the agent to call the Topaz endpoint shown on this page. The same RunAPI API key used for chat handles upscaling.

Is Topaz upscaling asynchronous?

Yes. The endpoint returns a task ID immediately, and OpenClaw polls the task status until the upscaled result is ready. RunAPI SDKs and the CLI handle polling automatically.

Does quality degrade on certain image types?

Topaz works best on photographic content. Heavily compressed images, very small sources, or images with existing AI artifacts can look over-smoothed at high scale factors, so test a smaller scale before running a batch.

Which model ID should I use?

Choose a public model ID from the version table. Each ID exposes the endpoints shown for that version.

Does this guide configure a chat model?

No. This Model Line uses the endpoint workflow shown here and is not presented as an agent chat model.

Start using Topaz with OpenClaw

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