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Qwen3 Coder Plus API: toman pricing and code

qwen/qwen3-coder-plus

toolsjson
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Input · per 1M tokens
188,581 toman
Output · per 1M tokens
942,906 toman
One 1,000-word request ≈
1,471 toman

You are billed for the usage the request actually reported. Prices follow the market. Cached input: 37,716 toman / 1M.Pricing and top-ups

Qwen3 Coder Plus example: tool calling

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-…")

tools = [{
    "type": "function",
    "function": {
        "name": "check_stock",
        "description": "Returns the stock level of a product",
        "parameters": {
            "type": "object",
            "properties": {"sku": {"type": "string"}},
            "required": ["sku"],
        },
    },
}]

messages = [{"role": "user", "content": "How many of the Nike NK-42 shoe are in stock?"}]
first = client.chat.completions.create(model="qwen/qwen3-coder-plus", messages=messages, tools=tools)
call = first.choices[0].message.tool_calls[0]

# you run the function yourself — the model never touches the database
args = json.loads(call.function.arguments)
result = {"sku": args["sku"], "qty": 7}

messages += [first.choices[0].message, {"role": "tool", "tool_call_id": call.id, "content": json.dumps(result)}]
final = client.chat.completions.create(model="qwen/qwen3-coder-plus", messages=messages, tools=tools)
print(final.choices[0].message.content)

What is Qwen3 Coder Plus good for?

Qwen3 Coder Plus comes from Qwen (Alibaba); in uttapen you reach it with the model id "qwen/qwen3-coder-plus". It accepts up to 1,000,000 tokens of input per call, so a long document or several source files fit in a single request. A single response can run to 65,536 tokens. On price it sits in the "mid-range" band — cheaper than 254 and dearer than 152 of the other paid models in the catalogue.

What you get on top of text in, text out: 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.

Input runs at 188,581 toman per 1M tokens and output at 942,906 — output costs 5× input, so trimming the answer saves more than trimming the prompt. It supports cached input: repeated context is billed at 37,716 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 DeepSeek V4 Pro 0813: Qwen3 Coder Plus 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 68 thousand-word requests on Qwen3 Coder Plus, and every 1,000 toman is about 680 words of round trip. A job with one million input tokens and one million output tokens comes to 1,131,488 toman in total. Filling this model's 1,000,000-token window costs 188,581 toman on the input side alone, which is the real reason to keep conversation history short.

Its nearest relative in the catalogue is "qwen/qwen3-coder-flash", and choosing between those two is where most people hesitate. On a thousand-word request this variant works out 3.3× dearer (1,471 against 441 toman). On parameters, this one takes structured_outputs.

Qwen (Alibaba) has 53 models in our catalogue; the cheapest is Qwen3.7 Flash at 60 toman per thousand words and the dearest Qwen3.8 Max (0902) at 3,017. Among the less common parameters it accepts logprobs, top_k, top_logprobs — all through the standard request body. It does not support include_reasoning, reasoning, 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 2 Lite at 1,000,000 tokens.

Where it makes sense: product chatbots and internal assistants, where cost and quality have to balance, 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

Qwen3 Coder Plus is Alibaba's proprietary version of the Open Source Qwen3 Coder 480B A35B. It is a powerful coding agent model specializing in autonomous programming via tool calling 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 out660 toman
Summarising a ten-page document4,000 in + 600 out1,320 toman
Classifying a thousand short rows120,000 in + 20,000 out41,488 toman

Frequently asked

How do I call Qwen3 Coder Plus 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 "qwen/qwen3-coder-plus". Nothing else in your code changes.
What does Qwen3 Coder Plus cost in toman?
188,581 toman per 1M input tokens and 942,906 toman per 1M output tokens; a 1,000-word request is around 1,471 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
How much input does Qwen3 Coder Plus take?
Up to 1,000,000 tokens per request, roughly 750k words. A single answer can reach 65,536 tokens.
Does Qwen3 Coder Plus support streaming and tool calling?
Streaming (stream=true) works on every model here. This one supports tool calling in the standard OpenAI shape. Structured output through response_format works too.