Hy4 API: toman pricing and code
tencent/hy4
You are billed for the usage the request actually reported. Prices follow the market. Cached input: 7,271 toman per 1M tokens.Pricing and top-ups
Hy4 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": "tencent/hy4",
"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="tencent/hy4",
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: "tencent/hy4",
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 Hy4 good for?
Hy4 comes from Tencent; in uttapen you reach it with the model id "tencent/
Capabilities available on this id: it reads images directly, which makes it a real option for invoices, forms and screenshots; 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 751 toman per 1,000-word exchange (144,373 in, 432,947 out, per 1M tokens). It supports cached input: repeated context is billed at 7,271 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 Gemini 3.5 Flash Lite (batch): Hy4 works out about 20% more expensive, and its context window is the same size. 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 133 thousand-word requests on Hy4, and every 1,000 toman is about 1,332 words of round trip. A job with one million input tokens and one million output tokens comes to 577,321 toman in total. Filling this model's 1,048,576-token window costs 151,387 toman on the input side alone, which is the real reason to keep conversation history short.
Tencent has 8 models in our catalogue; the cheapest is Hy-MT2-1.8B at 99 toman per thousand words and the dearest Hy4 preview at 1,501. Among the less common parameters it accepts max_completion_tokens, reasoning_effort — all through the standard request body. It does not support top_p, seed, 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 DeepSeek V4 Flash 0423 at 1,048,576 tokens.
What to use it for: 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.
The official release of Hy4 delivers comprehensive and substantial improvements over Hy4 Preview, with particularly strong gains in agentic capabilities and performance across a wide range of long-horizon, real-world productivity...
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 | 390 toman |
| Summarising a ten-page document | 4,000 in + 600 out | 837 toman |
| Classifying a thousand short rows | 120,000 in + 20,000 out | 25,984 toman |
Frequently asked
- How do I call Hy4 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 "tencent/ hy4". Nothing else in your code changes. - What does Hy4 cost in toman?
- 144,373 toman per 1M input tokens and 432,947 toman per 1M output tokens; a 1,000-word request is around 751 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
- How much input does Hy4 take?
- Up to 1,048,576 tokens per request, roughly 786k words. A single answer can reach 65,536 tokens.
- Does Hy4 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.