GPT-5.1 API: toman pricing and code
openai/gpt-5.1
You are billed for the usage the request actually reported. Prices follow the market. Cached input: 43,277 toman per 1M tokens. Web search: 3,462.19 toman per request.Pricing and top-ups
GPT-5.1 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-5.1",
"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-5.1",
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-5.1",
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-5.1 good for?
The id for GPT-5.1 in our API is "openai/
Capabilities available on this id: 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.
For a back-of-envelope figure: about 5,063 toman per 1,000-word exchange (432,774 in, 3,462,194 out, per 1M tokens). It supports cached input: repeated context is billed at 43,277 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 Opus 5.5 (batch): GPT-5.1 works out about 9% 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 20 thousand-word requests on GPT-5.1, and every 1,000 toman is about 198 words of round trip. A job with one million input tokens and one million output tokens comes to 3,894,968 toman in total. Filling this model's 400,000-token window costs 173,110 toman on the input side alone, which is the real reason to keep conversation history short.
Its nearest relative in the catalogue is "openai/
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.
What to use it for: product chatbots and internal assistants, where cost and quality have to balance, 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.
GPT-5.1 is the latest frontier-grade model in the GPT-5 series, offering stronger general-purpose reasoning, improved instruction adherence, and a more natural conversational style compared to GPT-5. It uses adaptive reasoning...
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 | 2,034 toman |
| Summarising a ten-page document | 4,000 in + 600 out | 3,808 toman |
| Classifying a thousand short rows | 120,000 in + 20,000 out | 121,177 toman |
Frequently asked
- How do I call GPT-5.1 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-5.1". Nothing else in your code changes. - What does GPT-5.1 cost in toman?
- 432,774 toman per 1M input tokens and 3,462,194 toman per 1M output tokens; a 1,000-word request is around 5,063 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
- How much input does GPT-5.1 take?
- Up to 400,000 tokens per request, roughly 300k words. A single answer can reach 128,000 tokens.
- Does GPT-5.1 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.