Model comparison
Compare GPT-Image-2.5 Flare and Reve 2.1 using the same provider-sourced image generation rubric. No mystery score and no invented benchmark ranking.
Facts checked September 9, 2026
Set your usage. Your estimate updates as you type.
Example output: square 1,024 × 1,024 images. Prices depend on supported resolution and quality; edits and retries can cost extra.
Estimates exclude taxes, tools, cache storage/writes, free allowances and custom discounts. Image estimates cover output only, not prompt or reference-image charges. Quality modes differ by model. Unlisted settings are not treated as free.
| Model | Access | Pricing & comparisons |
|---|---|---|
| GPT-Image-2.5 FlareOpenAI | OpenAI | $5 text input · $8 image input · $30 image output / 1M tokens |
| Reve 2.1Reve | Reve | No reviewed rate |
Quick take
OpenAI's speed-first GPT Image 2.5 model for everyday generation and editing, positioned at GPT Image 2-level image quality with lower latency.
Flare's speed positioning is a provider claim, not a fixed latency guarantee. Run repeated tests with the same prompt, references, dimensions, and quality before moving production traffic.
A typography-aware image model for creating and editing polished visuals, now available through Reve's creative product rather than its discontinued direct API.
The original Reve API is closed. Do not copy its former price or specifications onto a third-party endpoint, and check the product plan's model-improvement opt-out before using confidential brand assets.
Compare the published facts
Values use each provider's own published units and limits. A blank means the provider did not publish a directly comparable value in the sources reviewed.
| Image generation | GPT-Image-2.5 Flare | Reve 2.1 |
|---|---|---|
| Typical price basisA representative current provider price with its quality or resolution basis. | OpenAI: $5 text input · $8 image input · $30 image output / 1M tokens | Free, $7.99 Lite, or $19.99 Pro subscription |
| Maximum outputMaximum documented resolution or pixel area for the listed route. | Up to 3,840px per edge / 8.29MP | Up to native 4K / 16MP at launch |
| Core tasksWhether the model supports generation, editing, or both. | Generation and editing | Generation, editing, layout, and visual references |
| Reference imagesHow the model can use images to guide or edit an output. | Image inputs with improved subject preservation | Image references and editing in the Reve product |
| Text & layoutProvider-documented positioning for typography and structured composition. | Exact-text and structured-layout workflows | Designed for typography, layout, and prompt adherence |
| API accessDirect and notable third-party routes included in this guide. | OpenAI Images API, Responses tool | Original direct API closed; current access is the Reve product |
How to choose
Start with the job you need to complete, then validate cost, access, and policy details on your exact provider route.
OpenAI says direct API inputs and outputs are not used for model training by default. Standard abuse-monitoring retention and organization-specific data controls still apply.
Provider and API links
Reve says Free-plan content may be used for model improvement by default. Lite and Pro customers can opt out; verify the live account control before using confidential assets.
Provider and API links
Frequently asked questions
GPT-Image-2.5 Flare: OpenAI's speed-first GPT Image 2.5 model for everyday generation and editing, positioned at GPT Image 2-level image quality with lower latency. Reve 2.1: A typography-aware image model for creating and editing polished visuals, now available through Reve's creative product rather than its discontinued direct API.
Consider GPT-Image-2.5 Flare when your priority is Fast everyday image generation. Consider Reve 2.1 when your priority is Images that include typography or deliberate layout. Test both with your own data and provider route before committing.
No. This comparison aligns provider-published facts for the Image generation category. It does not claim a universal winner or combine incompatible third-party benchmark scores.
