Google: Nano Banana Pro (Gemini 3 Pro Image) vs Auto Code
A side-by-side comparison of Google: Nano Banana Pro (Gemini 3 Pro Image) ($7.00 / 1M tokens) and Auto Code ($105.00 / 1M tokens) using current USD prices and capabilities from the api14 catalog. Both run through the same OpenAI-compatible API.
Specifications
| Google: Nano Banana Pro (Gemini 3 Pro Image) | Auto Code | |
|---|---|---|
| Provider | OpenRouter | |
| Input | $7.00 / 1M tokens | $105.00 / 1M tokens |
| Output | $42.00 / 1M tokens | $630.00 / 1M tokens |
| Cache read | $0.70 / 1M tokens | - |
| Cache write | $1.31 / 1M tokens | - |
| Reasoning | $42.00 / 1M tokens | - |
| Image output | $420.00 / 1M tokens | - |
| Audio input | $7.00 / 1M tokens | - |
| Image | $0.000007 / image | - |
| Web search | $49.00 / 1K searches | - |
| Context window | 131,072 | 2,000,000 |
| Max output | 32,768 | 65,536 |
| Input | image, text | text, image, audio, file, video |
| Output | image, text | text, image |
| Tool calling | ||
| Structured output | ||
| Reasoning control | ||
| Added | Jun 18, 2026 | Nov 5, 2026 |
Key differences
- Google: Nano Banana Pro (Gemini 3 Pro Image) is 93% cheaper on input tokens.
- Google: Nano Banana Pro (Gemini 3 Pro Image) is 93% cheaper on output tokens.
- Auto Code reads 15.3× more context (2,000,000 tokens).
Switch with one string
Both models use the same endpoint and request shape. Change the model value from "google/gemini-3-pro-image" to "openrouter/auto-code" and prompts, streaming and tools keep working.
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": "openrouter/auto-code",
"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"));
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