# Starlight Precise 2.5

### Model Overview

**Starlight Precise 2.5** is a diffusion video enhancement model designed to improve realism in AI-generated video by reducing plastic or artificial artifacts. Building on Precise 2, it enhances facial detail while improving fabrics, materials, and the clarity of text, labels, and logos.

Precise 2.5 is well suited to upscale and enhance AI-generated footage that already has strong composition and structure but appears soft or slightly artificial. It also performs well on archival content where sufficient visual information exists, such as digital video footage from the 2000s onward.

### Key Capabilities

* Improved realism for AI-generated video with more natural faces, materials, and textures
* Enhanced rendering of text, labels, and fine detail for higher fidelity results
* Broad applicability across GenAI and modern archival footage with consistent, stable outputs

### Pricing

| Frames Per Credit — 1080p | Frames Per Credit — 4k |
| ------------------------- | ---------------------- |
| \~26                      | \~12                   |

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For more accurate estimates we recommend checking out our [Credit Calculator](https://developer.topazlabs.com/credit/calculator).
{% endhint %}

### Getting Started

**Endpoint**

* <https://api.topazlabs.com/video/>
  * `model` — `"slp-2.5"`

**Model-Specific Parameters**

* `input_frame_count` — integer, optional; maximum 9000
* `creativity` — `"low"`, `"middle"`, or `"high"`, optional
* `is_optimized_mode` — boolean, default true
* `enable_clc` — boolean, default true
* `video_profile` — string, optional
* `video_bit_depth` — integer, optional
* `video_codec` — string, optional

### Examples

<table data-card-size="large" data-view="cards"><thead><tr><th align="center"></th><th data-hidden data-card-cover data-type="image">Cover image</th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td align="center">Click to view</td><td><a href="https://4007072434-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FJkSwaYgAsTQke14gpXAF%2Fuploads%2FRbwNek2UdfbXUmpgpvmG%2Fvideo_21_slp2.5_slider.jpg?alt=media&#x26;token=6e24f448-93ea-4cb8-9e76-0281df9adcd5">video_21_slp2.5_slider.jpg</a></td><td><a href="https://compare.topazlabs.com/share/video/?src1=https%3A%2F%2Ftopazlabs.s3.us-east-1.amazonaws.com%2Fweb-assets%2Fmodel-examples%2Fvideo_21_veo3.1.mp4&#x26;src1label=Source&#x26;src2=https%3A%2F%2Ftopazlabs.s3.us-east-1.amazonaws.com%2Fweb-assets%2Fmodel-examples%2Fvideo_21_veo3.1_slp2.5.mp4&#x26;src2label=SLP%202.5&#x26;zoom=1&#x26;view=slider">https://compare.topazlabs.com/share/video/?src1=https%3A%2F%2Ftopazlabs.s3.us-east-1.amazonaws.com%2Fweb-assets%2Fmodel-examples%2Fvideo_21_veo3.1.mp4&#x26;src1label=Source&#x26;src2=https%3A%2F%2Ftopazlabs.s3.us-east-1.amazonaws.com%2Fweb-assets%2Fmodel-examples%2Fvideo_21_veo3.1_slp2.5.mp4&#x26;src2label=SLP%202.5&#x26;zoom=1&#x26;view=slider</a></td></tr><tr><td align="center">Click to view</td><td><a href="https://4007072434-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FJkSwaYgAsTQke14gpXAF%2Fuploads%2FaR0NsdYB5oRGjLfh1ny6%2Fvideo_45_slp2.5_slider.jpg?alt=media&#x26;token=a747797c-7ab4-41be-b775-9f812ca4fc33">video_45_slp2.5_slider.jpg</a></td><td><a href="https://compare.topazlabs.com/share/video/?src1=https%3A%2F%2Ftopazlabs.s3.us-east-1.amazonaws.com%2Fweb-assets%2Fmodel-examples%2Fvideo_45_veo3.1.mp4&#x26;src1label=Source&#x26;src2=https%3A%2F%2Ftopazlabs.s3.us-east-1.amazonaws.com%2Fweb-assets%2Fmodel-examples%2Fvideo_45_veo3.1_slp2.5.mp4&#x26;src2label=SLP%202.5&#x26;zoom=1&#x26;view=slider">https://compare.topazlabs.com/share/video/?src1=https%3A%2F%2Ftopazlabs.s3.us-east-1.amazonaws.com%2Fweb-assets%2Fmodel-examples%2Fvideo_45_veo3.1.mp4&#x26;src1label=Source&#x26;src2=https%3A%2F%2Ftopazlabs.s3.us-east-1.amazonaws.com%2Fweb-assets%2Fmodel-examples%2Fvideo_45_veo3.1_slp2.5.mp4&#x26;src2label=SLP%202.5&#x26;zoom=1&#x26;view=slider</a></td></tr></tbody></table>