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Aion 3.5 Mini API: toman pricing and code

aion-labs/aion-3.5-mini

Tool callingReasoningJSON output
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Input · per 1M tokens
242,354 toman
Output · per 1M tokens
484,707 toman
One 1,000-word request ≈
945 toman

You are billed for the usage the request actually reported. Prices follow the market. Cached input: 62,319 toman per 1M tokens.Pricing and top-ups

Aion 3.5 Mini 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="aion-labs/aion-3.5-mini", 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="aion-labs/aion-3.5-mini", messages=messages, tools=tools)
print(final.choices[0].message.content)
import OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.uttapen.ir/v1", apiKey: "sk-up-…" });

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

const messages = [{ role: "user", content: "How many of the Nike NK-42 shoe are in stock?" }];
const first = await client.chat.completions.create({ model: "aion-labs/aion-3.5-mini", messages, tools });
const call = first.choices[0].message.tool_calls[0];

const args = JSON.parse(call.function.arguments);
const result = { sku: args.sku, qty: 7 };

messages.push(first.choices[0].message, { role: "tool", tool_call_id: call.id, content: JSON.stringify(result) });
const final = await client.chat.completions.create({ model: "aion-labs/aion-3.5-mini", messages, tools });
console.log(final.choices[0].message.content);
curl https://api.uttapen.ir/v1/chat/completions \
  -H "Authorization: Bearer sk-up-…" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "aion-labs/aion-3.5-mini",
    "messages": [{"role": "user", "content": "How many of the Nike NK-42 shoe are in stock?"}],
    "tools": [{
      "type": "function",
      "function": {
        "name": "check_stock",
        "parameters": {"type": "object", "properties": {"sku": {"type": "string"}}, "required": ["sku"]}
      }
    }]
  }'

What is Aion 3.5 Mini good for?

Aion 3.5 Mini comes from Aion Labs; in uttapen you reach it with the model id "aion-labs/aion-3.5-mini". It accepts up to 262,144 tokens of input per call, so a long document or several source files fit in a single request. A single response can run to 32,768 tokens. On price it sits in the "cheap" band — cheaper than 221 and dearer than 174 of the other paid models in the catalogue.

Capabilities available on this id: 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 945 toman per 1,000-word exchange (242,354 in, 484,707 out, per 1M tokens). It supports cached input: repeated context is billed at 62,319 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 GLM 5.3: Aion 3.5 Mini works out about 40% more expensive, 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 106 thousand-word requests on Aion 3.5 Mini, and every 1,000 toman is about 1,058 words of round trip. A job with one million input tokens and one million output tokens comes to 727,061 toman in total. Filling this model's 262,144-token window costs 63,532 toman on the input side alone, which is the real reason to keep conversation history short.

Its nearest relative in the catalogue is "aion-labs/aion-3.0-mini", and choosing between those two is where most people hesitate. Both land at nearly the same price on a thousand-word request (945 and 945 toman). The context windows differ too: 262,144 against 131,072 tokens. On parameters, this one takes reasoning_effort.

Aion Labs has 6 models in our catalogue; the cheapest is Aion-3.0-Mini at 945 toman per thousand words and the dearest Aion 3.5 at 4,051. Among the less common parameters it accepts reasoning_effort — all through the standard request body. It does not support seed, structured_outputs, 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 Seed 1.6 at 262,144 tokens.

What to use it for: high-volume work such as classification, tagging and bulk summarising, logic puzzles and code review, 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

Aion 3.5 Mini is a multi-model roleplaying and storytelling system from AionLabs, built on the GLM family of models. It is the smaller, lower-cost sibling of Aion 3.5 and uses...

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 out557 toman
Summarising a ten-page document4,000 in + 600 out1,260 toman
Classifying a thousand short rows120,000 in + 20,000 out38,777 toman

Frequently asked

How do I call Aion 3.5 Mini 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 "aion-labs/aion-3.5-mini". Nothing else in your code changes.
What does Aion 3.5 Mini cost in toman?
242,354 toman per 1M input tokens and 484,707 toman per 1M output tokens; a 1,000-word request is around 945 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
How much input does Aion 3.5 Mini take?
Up to 262,144 tokens per request, roughly 197k words. A single answer can reach 32,768 tokens.
Does Aion 3.5 Mini 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.