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GPT-5.4 Pro API: toman pricing and code

openai/gpt-5.4-pro

Image inputTool callingReasoningJSON outputFile input
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Input · per 1M tokens
10,386,581 toman
Output · per 1M tokens
62,319,483 toman
One 1,000-word request ≈
94,518 toman

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

GPT-5.4 Pro 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.

# 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-5.4-pro",
    "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-5.4-pro",
    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-5.4-pro",
  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-5.4 Pro good for?

OpenAI publishes this model; we expose it under the id "openai/gpt-5.4-pro". Its context window is 1,050,000 tokens, roughly 788k English words in one request. A single response can run to 128,000 tokens. On price it sits in the "expensive" band, dearer than all 397 other paid models in the catalogue.

What it can do beyond plain text: 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.

Pricing is 10,386,581 toman per 1M input tokens and 62,319,483 per 1M output tokens. A 1,000-word round trip on GPT-5.4 Pro lands near 94,518 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 Claude Opus 4.1: GPT-5.4 Pro works out about 2.3× 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 1 thousand-word requests on GPT-5.4 Pro, and every 1,000 toman is about 11 words of round trip. A job with one million input tokens and one million output tokens comes to 72,706,064 toman in total. Filling this model's 1,050,000-token window costs 10,905,910 toman on the input side alone, which is the real reason to keep conversation history short.

Its nearest relative in the catalogue is "openai/gpt-5.5-pro", and choosing between those two is where most people hesitate. Both land at nearly the same price on a thousand-word request (94,518 and 94,518 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 MiMo-V2.5-Pro at 1,050,000 tokens.

Good fits: work where the quality of the answer matters more than its cost, 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-5.4 Pro is OpenAI's most advanced model, building on GPT-5.4's unified architecture with enhanced reasoning capabilities for complex, high-stakes tasks. It features a 1M+ token context window (922K input, 128K...

Three real jobs, priced on this model

Each figure is derived from the prices above and moves when they do.

JobTokensCost
One chat turn with a medium history1,500 in + 400 out40,508 toman
Summarising a ten-page document4,000 in + 600 out78,938 toman
Classifying a thousand short rows120,000 in + 20,000 out2,492,779 toman

Frequently asked

How do I call GPT-5.4 Pro 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-5.4-pro". Nothing else in your code changes.
What does GPT-5.4 Pro cost in toman?
10,386,581 toman per 1M input tokens and 62,319,483 toman per 1M output tokens; a 1,000-word request is around 94,518 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
How much input does GPT-5.4 Pro take?
Up to 1,050,000 tokens per request, roughly 788k words. A single answer can reach 128,000 tokens.
Does GPT-5.4 Pro 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.