The best AI image generator in Rivya is not one model for every job.

If you need the safest broad starting point, start with GPT Image 1.5. If you already know the image must behave like a shippable product or brand asset, Flux 2 Pro may be the better first run. If the real problem is taste and atmosphere, Midjourney deserves a serious test.

This guide is for choosing the first image path inside Rivya, not for ranking model names in isolation.

What We Evaluated

This guide was reviewed against Rivya's live image catalog on April 28, 2026. The recommendation is based on job fit inside Rivya, not a web-wide popularity ranking.

We checked:

current image model pages, including GPT Image 1.5, Flux 2 Pro, Midjourney, Nano Banana Pro, and Z-Image
supported input modes, reference behavior, credit hints, and first-run use cases
whether each model is better for discovery, product delivery, style exploration, finishing, or cheap draft testing
related product docs: Image Workflows, Models, and Image References

Quick Decision Table

Job shape	Start here	Why
Broad image work with mixed requirements	GPT Image 1.5	Balanced control, prompt obedience, and reference usefulness
Product, ecommerce, or brand asset	Flux 2 Pro	Better first fit when the image must feel usable and commercially controlled
Style exploration or campaign mood	Midjourney	Stronger when taste, atmosphere, and art direction matter most
Final polish after direction works	Nano Banana Pro	Better as a finishing pass than as a discovery tool
Cheap first learning pass	Z-Image	Useful when the goal is to test a direction before spending more credits

Use this table as the first cut. Then check references, placement, credit hints, and output settings on the model page.

Start With The Job Shape

Before choosing a model, write the image job in one sentence.

Examples:

Create a clean product image for an ecommerce listing.
Explore a premium visual mood for a launch campaign.
Generate a landing-page hero that still shows the product clearly.
Use references to keep the product shape and composition consistent.
Make a cheap first draft to test whether the direction is worth continuing.

Those are different jobs. They should not all start with the same model.

Broad Default: GPT Image 1.5

GPT Image 1.5 is the strongest broad default when the task is real but not yet narrow.

Use it when you need:

a balanced first answer
stronger prompt obedience
useful reference handling
a model that can survive mixed image requests
a first result that can narrow the workflow afterward

This is the right first stop when you cannot afford the first run to drift too far from the brief, but you have not yet decided the job is strictly ecommerce, ads, or style exploration.

Product Delivery: Flux 2 Pro

Flux 2 Pro becomes stronger when the output needs to behave like a real asset.

Use it for:

product stills
ecommerce visuals
packaging-visible images
brand-led commercial images
assets that need clarity before drama

If the image must survive a store page, landing page, or client review, delivery pressure matters more than broadness.

Style Exploration: Midjourney

Midjourney is stronger when the hardest part is taste.

Use it for:

editorial scenes
poster-like campaign visuals
atmospheric brand work
mood-led concept exploration
visuals where art direction matters more than strict execution

It is not always the safest delivery model, but it can be the better creative exploration tool.

Finishing: Nano Banana Pro

Nano Banana Pro is better after the direction already works.

Use it when you are asking:

can this look cleaner?
can this feel more premium?
is this close enough to justify a higher-fidelity pass?
do we need a final hero rather than another discovery run?

Do not use a finishing pass to discover the brief. Prove the direction first.

Low-Risk Drafts: Z-Image

Z-Image matters because not every idea deserves a high-cost first attempt.

Use it when you need to learn:

whether the composition works
whether the idea has potential
whether a stronger second pass is worth it
whether the prompt needs a different direction

Cheap learning is a real workflow stage.

How References Change The Choice

References can matter more than brand familiarity.

If the task depends on references, check:

whether the model accepts reference images
how many references it can use
whether references control product shape, style, layout, or previous output direction
whether the prompt explains what the reference should do

For reference-heavy work, pair this guide with Image References in Rivya and AI Image Generator With Reference Images.

First Run In Rivya

A good first image run looks like this:

Open the model page, such as GPT Image 1.5 or Flux 2 Pro.
Check supported modes, references, and credit hint.
Decide whether this is discovery, production, or finishing.
Enter one narrow prompt.
Upload references only when they are part of the task.
Review the result before increasing quality or switching models.

If you are already signed in and ready to run, continue through Image Studio. If you are still comparing, stay in the public model and image pages until the path is clearer.

When To Narrow The Choice

Use a narrower page when the task is already specific:

store-page or marketplace delivery
product-first image choice
paid ad creative
landing-page visual systems
product-photography art direction
heavy reference workflows

A broad guide is useful only while the decision is broad.

How To Test The Choice

Do not test every image model with a different prompt. That only tells you which prompt was better.

For a fair first comparison in Rivya:

Use one narrow task brief.
Keep the same subject, placement, reference role, and success criteria.
Run two or three likely candidates, not the whole catalog.
Judge the results against the job: obedience, product accuracy, visual taste, reference handling, artifacts, and credit comfort.
Only increase quality after one direction already works.

The winner is the model that moves the job forward with the least extra repair, not the one that produces the most impressive image in isolation.