Evidence boundary: This is an official-document comparison, not an APIDir image-quality benchmark. APIDir has not run controlled generations for these models, so this page does not name a quality, speed, or universal price winner.
Official API facts
| Decision dimension | GPT Image 2 | Nano Banana Pro |
|---|---|---|
| Canonical API identity | gpt-image-2; OpenAI also lists the pinned snapshot gpt-image-2-2026-04-21. | gemini-3-pro-image; Nano Banana Pro is Google's product name for Gemini 3 Pro Image. |
| Documented input and output | Text input plus image input and output; generation and edit endpoints are documented. | Text and image input; text and image output; image generation, thinking, and Search grounding are documented. |
| Standard image pricing | $8 per 1M image-input tokens, $2 cached image input, and $30 per 1M image-output tokens. Text input is $5 per 1M tokens, or $1.25 cached. | $2 per 1M text/image-input tokens. Image output is $120 per 1M tokens, documented as $0.134 for a 1K/2K image or $0.24 for a 4K image; text and thinking output is $12 per 1M tokens. |
| Lower-cost processing | OpenAI documents batch image-token prices at half the standard rates. | Google documents Batch and Flex image output at $0.067 for 1K/2K or $0.12 for 4K, plus separate Priority rates. |
| Operational features | Flexible image sizes and snapshot pinning are documented; streaming is not supported on the model page. | Batch, Flex, Priority, thinking, and Search grounding are documented. Generated images include SynthID. |
How to choose a route
- Short-list GPT Image 2 when OpenAI's image generation and editing endpoints, flexible image sizes, or a pinned model snapshot are requirements.
- Short-list Nano Banana Pro when Search grounding, thinking, 4K output, or a choice among Standard, Batch, Flex, and Priority processing is a requirement.
- Do not compare $30 and $120 token headlines as if they were the same meter. Fix model ID, size, quality, output count, reference inputs, processing tier, and retry policy, then compare the billed cost of successful outputs.
A benchmark that could support a real conclusion
- Freeze the exact model ID or snapshot, API route, region, account tier, image size, quality, output count, and reference assets.
- Run the same disclosed prompts across product fidelity, dense text, localization, reference identity, editing, and photorealistic tasks.
- Repeat every task enough times to expose variance; retain every output instead of selecting only the best result.
- Record latency, safety refusals, failed generations, retries, input and output usage, and total cost per accepted output.
- Publish the prompts, configuration, raw outputs, scoring rubric, reviewer method, date, and limitations before making a best-for claim.
Until that protocol has raw artifacts and repeatable results, APIDir treats quality, speed, reliability, and best-for claims as unverified.
First-party sources
- OpenAI GPT Image 2 modelOfficial model identity, modalities, endpoints, snapshot, and feature support; checked Aug 22, 2026.
- OpenAI API pricingOfficial standard and batch image-generation token rates; checked Aug 22, 2026.
- Google Gemini 3 Pro Image modelOfficial Nano Banana Pro model ID, modalities, limits, capabilities, and processing options; checked Aug 22, 2026.
- Google Gemini API pricingOfficial Standard, Batch, Flex, and Priority pricing units and per-image equivalents; checked Aug 22, 2026.
- Google image generation guideOfficial image-generation naming and SynthID disclosure; checked Aug 22, 2026.
Questions developers ask
Which API is cheaper, GPT Image 2 or Nano Banana Pro?
There is no valid universal answer from the headline token rates because token accounting, image size, quality, processing tier, and retries differ. Compare one fixed workload using actual billed usage.
Does APIDir claim that one model has better image quality?
No. This page compares current official documentation. APIDir has not published a controlled image-quality benchmark for these models.
What model IDs should an API test record?
Record gpt-image-2 or its pinned snapshot for OpenAI, and gemini-3-pro-image for Google's Nano Banana Pro, together with every request setting that can change output or cost.