GPT-5.2 Chat API: toman pricing and code
openai/gpt-5.2-chat
visiontoolsjsonfilesYou are billed for the usage the request actually reported. Prices follow the market. Cached input: 50,772 toman / 1M. Web search: 2,901.25 toman / request.Pricing and top-ups
GPT-5.2 Chat 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-5.2-chat",
"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-5.2-chat",
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-5.2-chat",
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-5.2 Chat good for?
GPT-5.2 Chat comes from OpenAI; in uttapen you reach it with the model id "openai/gpt-5.2-chat". It accepts up to 128,000 tokens of input per call, so a long document or several source files fit in a single request. A single response can run to 32,000 tokens. On price it sits in the "expensive" band — cheaper than 355 and dearer than 51 of the 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. All of it works through the standard parameters of the official OpenAI SDK — no custom client, no wrapper.
Pricing is 507,719 toman per 1M input tokens and 4,061,750 per 1M output tokens. A 1,000-word round trip on GPT-5.2 Chat lands near 5,940 toman. It supports cached input: repeated context is billed at 50,772 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 Claude Sonnet 4: GPT-5.2 Chat works out roughly 1.1× cheaper, and its context window is smaller. 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 17 thousand-word requests on GPT-5.2 Chat, and every 1,000 toman is about 168 words of round trip. A job with one million input tokens and one million output tokens comes to 4,569,469 toman in total. Filling this model's 128,000-token window costs 64,988 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-4o", and choosing between those two is where most people hesitate. On a thousand-word request this variant works out 1.3× dearer (5,940 against 4,715 toman). Maximum answer length differs as well: 32,000 against 16,384 tokens. On parameters the other takes frequency_penalty, logit_bias, logprobs, max_tokens.
OpenAI has 95 models in our catalogue; the cheapest is gpt-oss-20b at 60 toman per thousand words and the dearest o1-pro at 282,872. Among the less common parameters it accepts max_completion_tokens — all through the standard request body. It does not support include_reasoning, max_tokens, reasoning, temperature, 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 Nova Micro 1.0 at 128,000 tokens.
Good fits: work where the quality of the answer matters more than its cost, pulling text and fields out of images, agents that reach out to APIs and databases, extracting data against a fixed schema.
GPT-5.2 Chat (AKA Instant) is the fast, lightweight member of the 5.2 family, optimized for low-latency chat while retaining strong general intelligence. It uses adaptive reasoning to selectively “think” on...
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 | 2,386 toman |
| Summarising a ten-page document | 4,000 in + 600 out | 4,468 toman |
| Classifying a thousand short rows | 120,000 in + 20,000 out | 142,161 toman |
Frequently asked
- How do I call GPT-5.2 Chat 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-5.2-chat". Nothing else in your code changes.
- What does GPT-5.2 Chat cost in toman?
- 507,719 toman per 1M input tokens and 4,061,750 toman per 1M output tokens; a 1,000-word request is around 5,940 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
- How much input does GPT-5.2 Chat take?
- Up to 128,000 tokens per request, roughly 96k words. A single answer can reach 32,000 tokens.
- Does GPT-5.2 Chat 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.