Nano Banana 2 (Gemini 3.1 Flash Image) API: toman pricing and code
google/gemini-3.1-flash-image
You are billed for the usage the request actually reported. Prices follow the market. Per generated image: 20.77 toman. Web search: 4,847.07 toman per request.Pricing and top-ups
Nano Banana 2 (Gemini 3.1 Flash Image) example: image generation
The example is picked from this model's own capabilities. Drop in your key and it runs as is.
curl https://api.uttapen.ir/v1/chat/completions \
-H "Authorization: Bearer sk-up-…" \
-H "Content-Type: application/json" \
-d '{
"model": "google/gemini-3.1-flash-image",
"messages": [{"role": "user", "content": "A minimal photo of a coffee cup on a wooden table, natural light"}],
"modalities": ["image", "text"]
}'import base64
from openai import OpenAI
client = OpenAI(base_url="https://api.uttapen.ir/v1", api_key="sk-up-…")
resp = client.chat.completions.create(
model="google/gemini-3.1-flash-image",
messages=[{"role": "user", "content": "A minimal photo of a coffee cup on a wooden table, natural light"}],
extra_body={"modalities": ["image", "text"]},
)
# images are billed on image output tokens — check the balance before generating in bulk
for img in resp.choices[0].message.images or []:
data = img["image_url"]["url"].split(",", 1)[1]
open("out.png", "wb").write(base64.b64decode(data))
print("saved out.png")import OpenAI from "openai";
import { writeFileSync } from "node:fs";
const client = new OpenAI({ baseURL: "https://api.uttapen.ir/v1", apiKey: "sk-up-…" });
const resp = await client.chat.completions.create({
model: "google/gemini-3.1-flash-image",
messages: [{ role: "user", content: "A minimal photo of a coffee cup on a wooden table, natural light" }],
modalities: ["image", "text"],
});
for (const img of resp.choices[0].message.images ?? []) {
const b64 = img.image_url.url.split(",", 2)[1];
writeFileSync("out.png", Buffer.from(b64, "base64"));
}What is Nano Banana 2 (Gemini 3.1 Flash Image) good for?
The id for Nano Banana 2 (Gemini 3.1 Flash Image) in our API is "google/
What it can do beyond plain text: it reads images directly, which makes it a real option for invoices, forms and screenshots; it returns schema-valid JSON through response_format, ready to hand to your code; it has a reasoning mode that pays off on multi-step problems, maths and debugging; it can return generated images. All of it works through the standard parameters of the official OpenAI SDK — no custom client, no wrapper. Keep in mind that reasoning tokens are output tokens and do appear on the bill.
Pricing is 173,110 toman per 1M input tokens and 1,038,658 per 1M output tokens. A 1,000-word round trip on Nano Banana 2 (Gemini 3.1 Flash Image) lands near 1,575 toman. Each generated image costs around 20.77 toman. You are always charged for the usage the request actually reported, never for the estimate, and a failed request costs nothing.
The closest alternative with the same capabilities from a different provider is Moondream 3 Preview: Nano Banana 2 (Gemini 3.1 Flash Image) works out about 30% more expensive, and its context window is larger. Both run on the same key and the same code, so trying the other one is a single string change.
To make the figure concrete: 100,000 toman of credit buys roughly 63 thousand-word requests on Nano Banana 2 (Gemini 3.1 Flash Image), and every 1,000 toman is about 635 words of round trip. A job with one million input tokens and one million output tokens comes to 1,211,768 toman in total. Filling this model's 131,072-token window costs 22,690 toman on the input side alone, which is the real reason to keep conversation history short.
Its nearest relative in the catalogue is "google/
Google has 43 models in our catalogue; the cheapest is Gemma 4 26B A4B at 64 toman per thousand words and the dearest Gemini 3.1 Pro Preview Custom Tools at 6,301. Among the less common parameters it accepts reasoning_effort — all through the standard request body. It does not support tool_choice, tools, which most models here do, so test before switching if your code relies on them. By context size the nearest option from another provider is Aion-2.0 at 131,072 tokens.
Good fits: product chatbots and internal assistants, where cost and quality have to balance, logic puzzles and code review, pulling text and fields out of images, extracting data against a fixed schema.
Gemini 3.1 Flash Image, a.k.a. "Nano Banana 2," is Google’s latest state of the art image generation and editing model, delivering Pro-level visual quality at Flash speed. It combines advanced...
Three real jobs, priced on this model
Each figure is derived from the prices above and moves when they do.
| Job | Tokens | Cost |
|---|---|---|
| One chat turn with a medium history | 1,500 in + 400 out | 675 toman |
| Summarising a ten-page document | 4,000 in + 600 out | 1,316 toman |
| Classifying a thousand short rows | 120,000 in + 20,000 out | 41,546 toman |
Frequently asked
- How do I call Nano Banana 2 (Gemini 3.1 Flash Image) from Iran?
- Sign up with your mobile number, top the wallet up in toman, create an API key, then in the official OpenAI SDK point base_url at https:/
/ api.uttapen.ir/ v1 and set model to "google/ gemini-3.1-flash-image". Nothing else in your code changes. - What does Nano Banana 2 (Gemini 3.1 Flash Image) cost in toman?
- 173,110 toman per 1M input tokens and 1,038,658 toman per 1M output tokens; a 1,000-word request is around 1,575 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
- How much input does Nano Banana 2 (Gemini 3.1 Flash Image) take?
- Up to 131,072 tokens per request, roughly 98k words. A single answer can reach 32,768 tokens.
- Does Nano Banana 2 (Gemini 3.1 Flash Image) support streaming and image input?
- Streaming (stream=true) works on every model here. Image input is accepted through image_url, as a data URI or a public URL. Structured output through response_format works too.