How do I call GPT-5 Nano 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 "openai/gpt-5-nano". Nothing else in your code changes.

What does GPT-5 Nano cost in toman?

17,311 toman per 1M input tokens and 138,488 toman per 1M output tokens; a 1,000-word request is around 203 toman. You pay for the usage that request actually reported, and a failed request costs nothing.

How much input does GPT-5 Nano take?

Up to 400,000 tokens per request, roughly 300k words. A single answer can reach 128,000 tokens.

Does GPT-5 Nano support streaming and tool calling?

Streaming (stream=true) works on every model here. This one supports tool calling in the standard OpenAI shape. Image input is accepted through image_url, as a data URI or a public URL. Structured output through response_format works too.

GPT-5 Nano API: toman pricing and code

openai/gpt-5-nano

Image inputTool callingReasoningJSON outputFile input

Create a key Try it

Input · per 1M tokens

17,311 toman

Output · per 1M tokens

138,488 toman

One 1,000-word request ≈

203 toman

You are billed for the usage the request actually reported. Prices follow the market. Cached input: 1,731 toman per 1M tokens. Web search: 3,462.19 toman per request.Pricing and top-ups

GPT-5 Nano example: reading an image into JSON

The example is picked from this model's own capabilities. Drop in your key and it runs as is.

curlPythonNode.js

# tip: a data URI works too — base64 the file and prefix it with data:image/jpeg;base64,
curl https://api.uttapen.ir/v1/chat/completions \
  -H "Authorization: Bearer sk-up-…" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "openai/gpt-5-nano",
    "messages": [{
      "role": "user",
      "content": [
        {"type": "text", "text": "Return only the invoice number and the total, as JSON."},
        {"type": "image_url", "image_url": {"url": "https://example.com/factor.jpg"}}
      ]
    }]
  }'

import base64, json
from openai import OpenAI

client = OpenAI(base_url="https://api.uttapen.ir/v1", api_key="sk-up-…")

img = base64.b64encode(open("factor.jpg", "rb").read()).decode()

resp = client.chat.completions.create(
    model="openai/gpt-5-nano",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "Return the invoice number, the date and the total as JSON."},
            {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{img}"}},
        ],
    }],
    response_format={"type": "json_object"},
)
print(json.loads(resp.choices[0].message.content))

import OpenAI from "openai";
import { readFileSync } from "node:fs";

const client = new OpenAI({ baseURL: "https://api.uttapen.ir/v1", apiKey: "sk-up-…" });
const img = readFileSync("factor.jpg").toString("base64");

const resp = await client.chat.completions.create({
  model: "openai/gpt-5-nano",
  messages: [{
    role: "user",
    content: [
      { type: "text", text: "Return the invoice number, the date and the total as JSON." },
      { type: "image_url", image_url: { url: `data:image/jpeg;base64,${img}` } },
    ],
  }],
  response_format: { type: "json_object" },
});
console.log(JSON.parse(resp.choices[0].message.content));

What is GPT-5 Nano good for?

GPT-5 Nano comes from OpenAI; in uttapen you reach it with the model id "openai/gpt-5-nano". It accepts up to 400,000 tokens of input per call, so a long document or several source files fit in a single request. A single response can run to 128,000 tokens. On price it sits in the "very cheap" band — cheaper than 317 and dearer than 74 of the other paid models in the catalogue.

What you get on top of text in, text out: it reads images directly, which makes it a real option for invoices, forms and screenshots; it takes files such as PDFs as input; it supports tool calling, so it can invoke your own functions with valid arguments; 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. 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.

Input runs at 17,311 toman per 1M tokens and output at 138,488 — output costs 8× input, so trimming the answer saves more than trimming the prompt. It supports cached input: repeated context is billed at 1,731 toman per 1M, which matters a lot if your system prompt is long. 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 Seed-2.0-Mini: GPT-5 Nano works out about 9% cheaper, 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 493 thousand-word requests on GPT-5 Nano, and every 1,000 toman is about 4,926 words of round trip. A job with one million input tokens and one million output tokens comes to 155,799 toman in total. Filling this model's 400,000-token window costs 6,924 toman on the input side alone, which is the real reason to keep conversation history short.

This id gets confused with "openai/gpt-5-nano:batch", because the underlying model is the same. The difference is the suffix: no suffix (the standard variant) against "batch". On a thousand-word request this variant works out about 2× more expensive (203 against 101 toman). On parameters, this one takes max_completion_tokens.

OpenAI has 81 models in our catalogue; the cheapest is gpt-oss-20b (batch) at 61 toman per thousand words and the dearest GPT-5.5 Pro at 94,518. Among the less common parameters it accepts max_completion_tokens, reasoning_effort, verbosity — all through the standard request body. It does not support temperature, top_p, 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 Llama 4 Scout at 327,680 tokens.

Where it makes sense: high-volume work such as classification, tagging and bulk summarising, logic puzzles and code review, pulling text and fields out of images, agents that reach out to APIs and databases, extracting data against a fixed schema, analysing a long document or codebase in one request.

Provider's own description

GPT-5-Nano is the smallest and fastest variant in the GPT-5 system, optimized for developer tools, rapid interactions, and ultra-low latency environments. While limited in reasoning depth compared to its larger...

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	81 toman
Summarising a ten-page document	4,000 in + 600 out	152 toman
Classifying a thousand short rows	120,000 in + 20,000 out	4,847 toman

Job

Tokens

Cost

One chat turn with a medium history

1,500 in + 400 out

81 toman

Summarising a ten-page document

4,000 in + 600 out

152 toman

Classifying a thousand short rows

120,000 in + 20,000 out

4,847 toman

Other variants of this model

Same core model, different execution terms and different price. This page is the standard variant.

Variant	Model id	Output / 1M	Context
batch	openai/gpt-5-nano:batch	69,244	400,000

Variant

Model id

Output / 1M

Context

batch

openai/gpt-5-nano:batch

69,244

400,000

Put the variant's id verbatim in the model field; nothing else in your code changes.

Frequently asked

How do I call GPT-5 Nano 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 "openai/gpt-5-nano". Nothing else in your code changes.
What does GPT-5 Nano cost in toman?: 17,311 toman per 1M input tokens and 138,488 toman per 1M output tokens; a 1,000-word request is around 203 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
How much input does GPT-5 Nano take?: Up to 400,000 tokens per request, roughly 300k words. A single answer can reach 128,000 tokens.
Does GPT-5 Nano support streaming and tool calling?: Streaming (stream=true) works on every model here. This one supports tool calling in the standard OpenAI shape. Image input is accepted through image_url, as a data URI or a public URL. Structured output through response_format works too.