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Nano Banana 2.1 vs GPT Image 2.5 Sunburst: API price, context & features · api14

Google: Nano Banana 2.1 vs OpenAI: GPT Image 2.5 Sunburst

A side-by-side comparison of Google: Nano Banana 2.1 ($5.25 / 1M tokens) and OpenAI: GPT Image 2.5 Sunburst ($28.00 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.

Specifications

	Google: Nano Banana 2.1	OpenAI: GPT Image 2.5 Sunburst
Provider	Google	OpenAI
Input	$5.25 / 1M tokens	$28.00 / 1M tokens
Output	$26.25 / 1M tokens	$28.00 / 1M tokens
Image output	$105.00 / 1M tokens	$105.00 / 1M tokens
Web search	$49.00 / 1K searches	$35.00 / 1K searches
Cache read	-	$7.00 / 1M tokens
Context window	65,536	400,000
Max output	58,982	360,000
Input	image, text	text, image
Output	image, text	image
Tool calling
Structured output
Reasoning control
Added	Oct 6, 2026	Sep 9, 2026

Key differences

Google: Nano Banana 2.1 is 81% cheaper on input tokens.
Google: Nano Banana 2.1 is 6% cheaper on output tokens.
OpenAI: GPT Image 2.5 Sunburst reads 6.1× more context (400,000 tokens).
Only Google: Nano Banana 2.1 supports tool calling.
Only Google: Nano Banana 2.1 supports reasoning effort control.

In depth

Google: Nano Banana 2.1 is an image model from Google, and OpenAI: GPT Image 2.5 Sunburst is an image model from OpenAI. Both sit in the image category on api14, so neither is a general purpose text model you would reach for to draft documentation or answer support tickets. They are the two image options in this comparison, made by competing labs, and the choice between them comes down to how much context you need, whether you want text back alongside the image, and whether you need tool calling or reasoning controls.

The clearest split is context. GPT Image 2.5 Sunburst accepts up to 400,000 tokens, which is far larger than the 65,536 token window on Nano Banana 2.1, so long reference documents, big batches of source images or extended instructions fit more comfortably on the OpenAI model. Modalities differ too: Nano Banana 2.1 takes image and text as input and can return image and text as output, while GPT Image 2.5 Sunburst takes text and image in but returns image only. On parameters, Nano Banana 2.1 is the one that supports tools, tool choice and reasoning (including reasoning effort and include reasoning), and it also exposes temperature and top p, which GPT Image 2.5 Sunburst does not. Structured outputs and seed are available on both. Nano Banana 2.1 is the cheaper of the two on both input and output, so cost favors it if you are generating at volume.

For practical work, pick GPT Image 2.5 Sunburst when the job is mostly generation from a large body of context: a long brief, many reference images, or a prompt assembled from a big document, and when you only need an image back. Pick Nano Banana 2.1 when you want the model to call tools, when you want reasoning controls to shape how it works through a request, when you need a text answer returned next to the image, or when you want to tune sampling with temperature and top p. If your pipeline is cost sensitive and your prompts are short enough to fit in 65,536 tokens, Nano Banana 2.1 is the natural default.

Calling either one through api14 works the same way, because the gateway is OpenAI compatible. You point your existing client at api14, keep your usual request shape, and change only the model id: use "google/gemini-nano-banana-2.1" for the Google model or "openai/gpt-image-2.5-sunburst" for the OpenAI model. Everything else in the call, the messages, the image inputs and the response handling, stays as it is, so switching between the two for a test is a one line change rather than a rewrite.

There are still cases where the other model wins. If you need a very large context window, GPT Image 2.5 Sunburst is the better pick regardless of price, since Nano Banana 2.1 tops out much lower. If you need tool calling or reasoning parameters, the reverse holds and Nano Banana 2.1 is the only one of the two that offers them. Check the live price table on this page for current rates before you commit to either for a high volume job.

Switch with one string

Both models use the same endpoint and request shape. Change the model value from "google/gemini-nano-banana-2.1" to "openai/gpt-image-2.5-sunburst" and prompts, streaming and tools keep working.

Google: Nano Banana 2.1 details & playground →OpenAI: GPT Image 2.5 Sunburst details & playground →

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api14.com/api/v1",
  apiKey: process.env.API14_API_KEY,
});

const result = await client.images.generate({
  "model": "openai/gpt-image-2.5-sunburst",
  "prompt": "A minimalist product photo of a ceramic mug on a wooden table",
  "n": 1,
  "aspect_ratio": "1:1"
});
import { writeFile } from "node:fs/promises";
await writeFile("image.png", Buffer.from(result.data[0].b64_json, "base64"));

Google: Nano Banana 2.1 vs OpenAI: GPT Image 2.5 Sunburst

Specifications

Key differences

In depth

Switch with one string

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