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Hy-MT2-30B-A3B API: toman pricing and code

tencent/hy-mt2-30b-a3b

json
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Input · per 1M tokens
21,469 toman
Output · per 1M tokens
85,587 toman
One 1,000-word request ≈
139 toman

You are billed for the usage the request actually reported. Prices follow the market.Pricing and top-ups

Hy-MT2-30B-A3B example: JSON output against a schema

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

from openai import OpenAI
import json

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

schema = {
    "name": "ticket",
    "schema": {
        "type": "object",
        "properties": {
            "category": {"type": "string", "enum": ["fani", "mali", "forush"]},
            "priority": {"type": "integer", "minimum": 1, "maximum": 5},
            "summary": {"type": "string"},
        },
        "required": ["category", "priority", "summary"],
        "additionalProperties": False,
    },
    "strict": True,
}

resp = client.chat.completions.create(
    model="tencent/hy-mt2-30b-a3b",
    messages=[{"role": "user", "content": "Ticket: "For two days I cannot download my invoice and I was charged twice.""}],
    response_format={"type": "json_schema", "json_schema": schema},
)
print(json.loads(resp.choices[0].message.content))

What is Hy-MT2-30B-A3B good for?

Hy-MT2-30B-A3B is one of Tencent's models. Put "tencent/hy-mt2-30b-a3b" in the model field and the rest of your code stays as it is. Hy-MT2-30B-A3B keeps 8,192 tokens in view at once, and that number is what caps the conversation history in your product. A single response can run to 4,096 tokens. On price it sits in the "very cheap" band — cheaper than 59 and dearer than 347 of the other paid models in the catalogue.

Capabilities available on this id: 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.

For a back-of-envelope figure: about 139 toman per 1,000-word exchange (21,469 in, 85,587 out, per 1M tokens). 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 Llama 3.2 3B Instruct: Hy-MT2-30B-A3B works out roughly 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 719 thousand-word requests on Hy-MT2-30B-A3B, and every 1,000 toman is about 7,194 words of round trip. A job with one million input tokens and one million output tokens comes to 107,056 toman in total. Filling this model's 8,192-token window costs 176 toman on the input side alone, which is the real reason to keep conversation history short.

Its nearest relative in the catalogue is "tencent/hy-mt2-7b", and choosing between those two is where most people hesitate. Both land at nearly the same price on a thousand-word request (139 and 139 toman).

Tencent has 7 models in our catalogue; the cheapest is Hy-MT2-1.8B at 83 toman per thousand words and the dearest Hy4 preview at 1,258. Among the less common parameters it accepts max_completion_tokens — all through the standard request body. It does not support include_reasoning, reasoning, tool_choice, tools, 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 R1 Distill Llama 70B at 8,192 tokens.

What to use it for: high-volume work such as classification, tagging and bulk summarising, extracting data against a fixed schema, short single-turn requests (the context window is small).

Provider's own description

Hy-MT2-30B-A3B is Tencent's flagship translation model in the Hy-MT2 family. It supports 33 language pairs and five Chinese dialect and minority-language pairs, with workflows for structured, delimiter-based, contextual, glossary-based, and...

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 out66 toman
Summarising a ten-page document4,000 in + 600 out137 toman
Classifying a thousand short rows120,000 in + 20,000 out4,288 toman

Frequently asked

How do I call Hy-MT2-30B-A3B 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/hy-mt2-30b-a3b". Nothing else in your code changes.
What does Hy-MT2-30B-A3B cost in toman?
21,469 toman per 1M input tokens and 85,587 toman per 1M output tokens; a 1,000-word request is around 139 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
How much input does Hy-MT2-30B-A3B take?
Up to 8,192 tokens per request, roughly 6k words. A single answer can reach 4,096 tokens.
Can I stream Hy-MT2-30B-A3B's output?
Yes — with stream=true you get SSE events as the tokens are produced. This model has no tool calling and no image input, so pick a different one if you need either.