Nano Banana 2 vs GPT Image 1.5 in 2026: Which Image API Fits Your Workflow?
- Nano Banana 2 is easier to think about when you want a fast image-generation-and-editing route with clear per-image pricing on EvoLink.
- GPT Image 1.5 is easier to think about when you want OpenAI's official image model docs and a pricing model tied directly to image quality tiers.
TL;DR
- Choose Nano Banana 2 when you want a route built around image generation and editing with explicit 1K, 2K, and 4K pricing on EvoLink.
- Choose GPT Image 1.5 when you want OpenAI's official pricing and docs for a flagship image model.
- This should be a workflow-fit decision, not a winner-style headline.
What is officially documented
| Model | What is clearly documented | Pricing shape | Best fit |
|---|---|---|---|
| Nano Banana 2 | Google's official materials identify it as Gemini 3.1 Flash Image; EvoLink documents generation and editing routes plus 1K / 2K / 4K price tiers | Per-image route pricing on EvoLink | Teams that want image generation and editing with clear route-based pricing |
| GPT Image 1.5 | OpenAI documents GPT Image 1.5 as a state-of-the-art image generation model and publishes per-image quality pricing | Per-image cost by quality and size in OpenAI docs | Teams that want OpenAI's direct image model workflow |
Nano Banana 2: the case for a route-first image workflow
Current route signals on EvoLink
| Output tier | Current listed route price |
|---|---|
1K | $0.0538/image |
2K | $0.0806/image |
4K | $0.1210/image |
That is useful when finance wants predictable per-image budgeting rather than token estimation.
When Nano Banana 2 is the better fit
Choose Nano Banana 2 if you care most about:
- a route that handles both image generation and editing
- explicit 1K / 2K / 4K price tiers
- a workflow that can stay inside a gateway you already use for other models
GPT Image 1.5: the case for direct OpenAI image workflows
- token pricing on the model page
- approximate per-image cost by quality on the pricing page
Current official OpenAI price signals
| Quality | Approximate square-image cost |
|---|---|
| Low | $0.01 |
| Medium | $0.04 |
| High | $0.17 |
That makes GPT Image 1.5 easy to justify when:
- your team prefers official OpenAI docs as the source of record
- you want to align image work with the rest of an OpenAI-native stack
- you are already using OpenAI tooling and account workflows
A better comparison than "which looks better?"
The weaker version of this article would try to declare one universal quality winner. The stronger version compares the buying shape.
| If your main priority is... | Start with | Why |
|---|---|---|
| Clear route pricing by output tier | Nano Banana 2 | EvoLink publishes route prices for 1K / 2K / 4K |
| Official OpenAI documentation | GPT Image 1.5 | OpenAI publishes the model docs and image pricing directly |
| Unified gateway workflow | Nano Banana 2 on EvoLink | Useful if you are already routing other models through one API |
| OpenAI-native stack consistency | GPT Image 1.5 | Cleaner fit if your app already depends on OpenAI account and tooling flows |
FAQ
What is Nano Banana 2 officially called?
Does Nano Banana 2 support editing as well as generation?
Yes. The current Google and EvoLink materials both position it around generation and editing workflows.
How does GPT Image 1.5 pricing work?
OpenAI documents both token-based pricing and approximate per-image pricing by quality tier.
Which model is easier to budget per image?
Nano Banana 2 on EvoLink is easier if you want explicit route prices by output tier. GPT Image 1.5 is easier if you want OpenAI's official quality-based cost signals.
Is this article claiming one model is universally better?
No. The safer conclusion is that they fit different production preferences.
Which should I pick for an OpenAI-first stack?
GPT Image 1.5 is the cleaner starting point if your app already depends on OpenAI workflows and account management.
Try Both Image Routes in One Stack
If you want to compare Nano Banana 2, GPT Image 1.5, and other image models without changing your app around every provider separately, EvoLink is the practical route.
Compare Image Models on EvoLink
