Best AI Image-to-Image Generators 2026
Compare 2026 image-to-image generators including GPT-Image 2.0 and FLUX Kontext. See credit costs, resolution limits, and how to keep reference fidelity across edits.
TL;DR
GPT-Image 2.0 at 8 credits per 1024 job with full masks offers the best balance for character series work. FLUX Kontext costs 11 credits but keeps sharper edges on line art. Start at the Image to Image page and lock the reference seed to avoid drift.
Starting with a concrete cost problem
Generating a variation from an existing 1024x1024 reference on most platforms consumes 12 credits and still alters facial details by the third pass. Users hit this wall when they need the same character across five frames without redrawing from scratch.
The usual workaround of uploading to a new text prompt session loses the original composition 70 percent of the time after two iterations. That forces extra manual masking steps that add 15 minutes per asset.
Where standard tools fall short
Midjourney's remix mode applies global style shifts even at low strength settings. DALL-E variations ignore precise mask inputs beyond simple rectangular regions. Both require separate upscaling passes that double the credit spend.
Method that preserves reference data
Flixly's dedicated workflow accepts a source image plus optional mask at the Image to Image page. It routes the job to GPT-Image 2.0 by default, which supports 2048-pixel inputs and returns outputs in under 8 seconds for standard jobs.
Users can switch the backend model selector to FLUX Kontext for higher edge fidelity on line art. A single run with strength set to 0.65 keeps 92 percent of original pixel positions while allowing targeted color swaps.
Comparison of 2026 image-to-image backends
| Model | Max input size | Typical credits | Mask support | Output formats |
|---|---|---|---|---|
| GPT-Image 2.0 | 2048 px | 8 | Full | PNG, JPG, WebP |
| FLUX Kontext | 1536 px | 11 | Edge only | PNG, TIFF |
| Gemini 3.1 Flash | 1024 px | 6 | Rectangular | JPG, WebP |
The table shows tradeoffs between resolution and cost. GPT-Image 2.0 balances both for most character work.
Edge cases and remaining limits
When the reference contains fine text or logos, even FLUX Kontext drops legibility below 0.4 strength. In those cases the AI Photo Effects pipeline lets you apply a separate sharpening pass afterward.
Transparent backgrounds trigger an extra compositing step that adds 3 credits. The system returns an alpha channel only when the source file already contains one.
Long sessions with repeated uploads hit daily generation caps after 40 jobs on the starter credit pack. Paid plans raise the limit to 200.
Workflow for consistent series output
Upload the base frame to Image to Image. Enable the reference lock toggle. Generate three variants at 0.55 strength, then feed the best one into Image to Image again with a new mask for clothing changes. Track versions by appending _v02 to the filename before the next round.
For product shots the same chain works with Product Mockup as the final stage to place the edited item on a neutral background.
FAQ
What resolution should I start with for character consistency? Begin at 1024x1024 when testing. Move to 1536 or 2048 only after confirming the model keeps facial landmarks intact at lower settings.
How many credits does a masked edit on GPT-Image 2.0 use? A 1024-square job with a 40 percent mask area costs 8 credits and returns in 6-9 seconds.
Can I keep the same seed across multiple image-to-image passes? Yes. The seed field accepts manual entry and stays fixed until you change it, allowing reproducible edits on the same reference.
Does FLUX Kontext handle anime line art better than GPT-Image 2.0? FLUX Kontext retains clean edges on black-and-white sketches at strength 0.7 while GPT-Image 2.0 tends to soften lines unless post-processed.
What file formats are accepted as references? PNG, JPG, and WebP up to 10 MB. TIFF is supported only on the FLUX Kontext route.
Frequently Asked Questions
What resolution should I start with for character consistency?▾
Begin at 1024x1024 when testing. Move to 1536 or 2048 only after confirming the model keeps facial landmarks intact at lower settings.
How many credits does a masked edit on GPT-Image 2.0 use?▾
A 1024-square job with a 40 percent mask area costs 8 credits and returns in 6-9 seconds.
Can I keep the same seed across multiple image-to-image passes?▾
Yes. The seed field accepts manual entry and stays fixed until you change it, allowing reproducible edits on the same reference.
Does FLUX Kontext handle anime line art better than GPT-Image 2.0?▾
FLUX Kontext retains clean edges on black-and-white sketches at strength 0.7 while GPT-Image 2.0 tends to soften lines unless post-processed.
What file formats are accepted as references?▾
PNG, JPG, and WebP up to 10 MB. TIFF is supported only on the FLUX Kontext route.
