How Autotube uses GPT Image 2.5 Flare.
2K output that composes as a full 1080p scene frame, at a value-tier price — and the 1080p-class model your own Replicate key covers, which is what sets it apart from the cheaper default.
4 credits per image
Why GPT Image 2.5 Flare is in the catalog.
1080p on your own key
2K output composed as a full 1080p scene frame, and your own Replicate key can cover it, so an Own Keys run pays the provider directly rather than spending credits.
Every scene in one run
It runs as a whole-video batch, so a fifty-scene explainer is generated in one pass rather than scene by scene.
Cast and look hold
Characters stay consistent from the project's reference images, and a style reference goes in the same request.
When a video looks soft
It is the model to try first when a video looks soft and the bill has to stay where it is: 1080p scene frames across a long video rather than on a handful of hero shots.
Specs, from the app’s own catalog
- Output size
- 2K images, 1080p scene frames
- Consistent characters
- Yes, from reference images
- Reference images
- Up to 10 per scene
- Style reference
- Yes, alongside character references
- Match an input image
- No, a preset ratio only
- Prompt length
- No fixed cap
- Whole-video batches
- Yes, every scene in one run
Priced in credits, before it runs.
4 credits per image
Flat per image at the settings Autotube's visuals run on, so the figure above holds across a whole scene list regardless of prompt length or reference count. The default model is cheaper still, so the reason to choose this one is the Replicate route: on your own key it costs you the provider's price and no credits at all.
GPT Image 2.5 Flare against the other image models.
| Muse Image | Nano Banana 2.1 | Grok Imagine | GPT Image 2 | GPT Image 2.5 Flare | |
|---|---|---|---|---|---|
| Credits | 3 credits per image | 11 credits per image | 6 credits per image | Priced from the request | 4 credits per image |
| Output size | 2K images, 1080p scene frames | 1K images, 720p scene frames | 2K images, 1080p scene frames | 1K images, 720p scene frames | 2K images, 1080p scene frames |
| Consistent characters | Yes, from reference images | Yes, from reference images | Yes, from reference images | Yes, from reference images | Yes, from reference images |
| Reference images | Up to 10 per scene | Up to 14 per scene | Up to 5 per scene | Up to 10 per scene | Up to 10 per scene |
| Style reference | Yes, alongside character references | Yes, alongside character references | Yes, alongside character references | Yes, alongside character references | Yes, alongside character references |
| Match an input image | No, a preset ratio only | No, a preset ratio only | Yes, instead of a preset ratio | No, a preset ratio only | No, a preset ratio only |
| Prompt length | No fixed cap | No fixed cap | No fixed cap | No fixed cap | No fixed cap |
| Whole-video batches | Yes, every scene in one run | Yes, every scene in one run | Yes, every scene in one run | No, one image at a time | Yes, every scene in one run |
What GPT Image 2.5 Flare will not do.
- It is a still-image model; a scene that needs motion belongs on a video model.
- Its reference budget, while generous, is below the largest in the catalog — the spec table has the exact figure.
GPT Image 2.5 Flare: common questions
The rest of the catalog.
Try GPT Image 2.5 Flare on your next video.
Every plan reaches every model in the catalog, and the app shows the exact credit cost before it runs a thing.