Models and options
The built-in image generators, with their resolutions, aspect ratios and model-specific controls.
Every model exposes its own controls, because the services genuinely differ. Google and ByteDance models think in aspect ratios and a resolution tier; OpenAI models think in fixed pixel sizes; the OpenRouter models take an aspect ratio and set the resolution themselves. Monet shows you whichever set applies to the model you picked.
The table lists the models Monet ships with. It is not necessarily the whole list: providers you add yourself pull their own models in, and Settings → Models keeps the full, current registry — where you can hide a model from the picker, rename it, choose its colour, or set its default options. See Settings.
| Model | Service | Resolution | Notes |
|---|---|---|---|
| Nanobanana Progemini-3-pro-image-preview | Google Gemini | 1K, 2K, 4K | 10 aspect ratios, from 1:1 to 21:9. Defaults to 2K. |
| Nanobanana 2gemini-3.1-flash-image-preview | Google Gemini | 512, 1K, 2K, 4K | 14 aspect ratios, adding banner and panorama shapes such as 4:1 and 8:1. Defaults to 1K. |
| GPT Image 2gpt-image-2 | OpenAI | Up to 3840×2160 | Fixed sizes rather than ratios. Quality, background, output format (PNG, JPEG, WebP) and moderation level. |
| GPT Image 1.5gpt-image-1.5 | OpenAI | Up to 1536×1024 | Quality, background (including transparent) and output format. |
| Seedream 5.0 Proseedream-5.0-pro | ByteDance, via fal.ai | 1K, 2K | 14 aspect ratios and reference-image editing. Defaults to 2K. |
| FLUX.2 Problack-forest-labs/flux.2-pro | OpenRouter | Set by the model | 10 aspect ratios, from 1:1 to 21:9. No resolution tiers; defaults to 1:1. |
| Riverflow V2.5 Prosourceful/riverflow-v2.5-pro | OpenRouter | Set by the model | The same 10 aspect ratios as FLUX.2 Pro, defaulting to 1:1. |
Shared options
- Aspect ratio. Square, portrait, landscape and widescreen shapes, up to ultra-wide 21:9. Nanobanana 2 and Seedream add extreme banner shapes such as 4:1, 1:4, 8:1 and 1:8.
- Resolution. 512 for quick drafts, 1K for everyday work, 2K for detail, and 4K where the model supports it. Larger images take longer and cost more.
- Reference images. Attach existing images to steer the result. This is what keeps a subject recognisable between runs, so it matters most when you are regenerating a layer.
OpenAI-only options
- Quality. Auto, high, medium or low, trading detail against speed.
- Background. Auto or opaque, and on GPT Image 1.5, transparent, which is handy for layers you plan to composite.
- Output format. PNG for lossless and transparency, JPEG for smaller files, or WebP.
- Moderation. Auto or low, controlling how strict OpenAI’s content filtering is.