Aion-3.0 API: toman pricing and code
aion-labs/aion-3.0
You are billed for the usage the request actually reported. Prices follow the market. Cached input: 259,665 toman per 1M tokens.Pricing and top-ups
Aion-3.0 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="aion-labs/aion-3.0",
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))import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.uttapen.ir/v1", apiKey: "sk-up-…" });
const resp = await client.chat.completions.create({
model: "aion-labs/aion-3.0",
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: {
name: "ticket",
strict: true,
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,
},
},
},
});
console.log(JSON.parse(resp.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-3.0",
"messages": [{"role": "user", "content": "Classify the ticket and give it a priority from 1 to 5."}],
"response_format": {"type": "json_object"}
}'What is Aion-3.0 good for?
Aion Labs publishes this model; we expose it under the id "aion-labs/
What it can do beyond plain text: 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.
Pricing is 1,038,658 toman per 1M input tokens and 2,077,316 per 1M output tokens. A 1,000-word round trip on Aion-3.0 lands near 4,051 toman. It supports cached input: repeated context is billed at 259,665 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 Mistral Large: Aion-3.0 works out about 10% more expensive, and its context window is larger. 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 25 thousand-word requests on Aion-3.0, and every 1,000 toman is about 247 words of round trip. A job with one million input tokens and one million output tokens comes to 3,115,974 toman in total. Filling this model's 131,072-token window costs 136,139 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 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. 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 Nano Banana Pro (Gemini 3 Pro Image) at 131,072 tokens.
Good fits: product chatbots and internal assistants, where cost and quality have to balance, logic puzzles and code review, agents that reach out to APIs and databases, extracting data against a fixed schema.
Aion-3.0 is a multi-model roleplaying and storytelling system from AionLabs, built on the GLM family of models. It uses a collaborative generation process in which multiple specialized models each contribute...
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 | 2,389 toman |
| Summarising a ten-page document | 4,000 in + 600 out | 5,401 toman |
| Classifying a thousand short rows | 120,000 in + 20,000 out | 166,185 toman |
Frequently asked
- How do I call Aion-3.0 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-3.0". Nothing else in your code changes. - What does Aion-3.0 cost in toman?
- 1,038,658 toman per 1M input tokens and 2,077,316 toman per 1M output tokens; a 1,000-word request is around 4,051 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
- How much input does Aion-3.0 take?
- Up to 131,072 tokens per request, roughly 98k words. A single answer can reach 32,768 tokens.
- Does Aion-3.0 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.