Qwen2.5 Coder 32B Instruct API: toman pricing and code
qwen/qwen-2.5-coder-32b-instruct
You are billed for the usage the request actually reported. Prices follow the market.Pricing and top-ups
Qwen2.5 Coder 32B Instruct example: summarising a document
The example is picked from this model's own capabilities. Drop in your key and it runs as is.
from openai import OpenAI
client = OpenAI(base_url="https://api.uttapen.ir/v1", api_key="sk-up-…")
stream = client.chat.completions.create(
model="qwen/qwen-2.5-coder-32b-instruct",
messages=[{"role": "user", "content": "Summarise this text in three sentences:
\"This year's budget act makes three main changes…\""}],
stream=True,
)
for chunk in stream:
print(chunk.choices[0].delta.content or "", end="", flush=True)import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.uttapen.ir/v1", apiKey: "sk-up-…" });
const stream = await client.chat.completions.create({
model: "qwen/qwen-2.5-coder-32b-instruct",
messages: [{ role: "user", content: "Summarise this text in three sentences:
\"This year's budget act makes three main changes…\"" }],
stream: true,
});
for await (const chunk of stream) process.stdout.write(chunk.choices[0]?.delta?.content ?? "");curl https://api.uttapen.ir/v1/chat/completions \
-H "Authorization: Bearer sk-up-…" \
-H "Content-Type: application/json" \
-d '{
"model": "qwen/qwen-2.5-coder-32b-instruct",
"messages": [{"role": "user", "content": "Summarise this text in three sentences: \"This year's budget act makes three main changes…\""}],
"stream": true
}'What is Qwen2.5 Coder 32B Instruct good for?
Qwen (Alibaba) publishes this model; we expose it under the id "qwen/qwen-2.5-coder-32b-instruct". Its context window is 32,768 tokens, roughly 25k English words in one request. A single response can run to 29,491 tokens. On price it sits in the "cheap" band — cheaper than 135 and dearer than 271 of the other paid models in the catalogue.
This one handles text only. If you need function calling or image understanding, pick another model from the same catalogue — swapping is a one-line change.
For a back-of-envelope figure: about 626 toman per 1,000-word exchange (191,483 in, 290,125 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 Hermes 3 405B Instruct: Qwen2.5 Coder 32B Instruct works out roughly 1.2× 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 160 thousand-word requests on Qwen2.5 Coder 32B Instruct, and every 1,000 toman is about 1,597 words of round trip. A job with one million input tokens and one million output tokens comes to 481,608 toman in total. Filling this model's 32,768-token window costs 6,274 toman on the input side alone, which is the real reason to keep conversation history short.
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 logit_bias, min_p, repetition_penalty, top_k — all through the standard request body. It does not support include_reasoning, reasoning, response_format, tool_choice, 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 Aion-RP 1.0 (8B) at 32,768 tokens.
What to use it for: high-volume work such as classification, tagging and bulk summarising.
Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (formerly known as CodeQwen). Qwen2.5-Coder brings the following improvements upon CodeQwen1.5: - Significantly improvements in **code generation**, **code 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 | 403 toman |
| Summarising a ten-page document | 4,000 in + 600 out | 940 toman |
| Classifying a thousand short rows | 120,000 in + 20,000 out | 28,780 toman |
Frequently asked
- How do I call Qwen2.5 Coder 32B Instruct 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/qwen-2.5-coder-32b-instruct". Nothing else in your code changes.
- What does Qwen2.5 Coder 32B Instruct cost in toman?
- 191,483 toman per 1M input tokens and 290,125 toman per 1M output tokens; a 1,000-word request is around 626 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
- How much input does Qwen2.5 Coder 32B Instruct take?
- Up to 32,768 tokens per request, roughly 25k words. A single answer can reach 29,491 tokens.
- Can I stream Qwen2.5 Coder 32B Instruct'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.