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Aion 3.5 API: toman pricing and code

aion-labs/aion-3.5

Tool callingReasoningJSON output
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Input · per 1M tokens
1,038,658 toman
Output · per 1M tokens
2,077,316 toman
One 1,000-word request ≈
4,051 toman

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 3.5 example: a multi-step problem with reasoning

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-…")

resp = client.chat.completions.create(
    model="aion-labs/aion-3.5",
    messages=[{"role": "user", "content": (
        "A shop has 3 warehouses. A ships 120 orders a day, B ships 85 and C ships 40. "
        "If C closes and its load is split between A and B in proportion to their capacity, how many does each ship a day? "
        "Work through it step by step and give just the two numbers at the end."
    )}],
    reasoning_effort="medium",   # low | medium | high
)
print(resp.choices[0].message.content)
# reasoning tokens count as output tokens too:
print(resp.usage.completion_tokens_details)
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",
    "messages": [{"role": "user", "content": "120 and 85 daily orders split across two warehouses; work through it step by step."}],
    "reasoning": {"effort": "medium"}
  }'
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-3.5",
  messages: [{ role: "user", content: "120 and 85 daily orders are split between two warehouses; work through it step by step and give just the two numbers at the end." }],
  reasoning_effort: "medium",
});
console.log(resp.choices[0].message.content);
console.log(resp.usage.completion_tokens_details);

What is Aion 3.5 good for?

Aion 3.5 comes from Aion Labs; in uttapen you reach it with the model id "aion-labs/aion-3.5". 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 "mid-range" band — cheaper than 92 and dearer than 291 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; 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.

Input runs at 1,038,658 toman per 1M tokens and output at 2,077,316 — output costs 2× input, so trimming the answer saves more than trimming the prompt. 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 3.5 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 3.5, 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 262,144-token window costs 272,278 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", and choosing between those two is where most people hesitate. Both land at nearly the same price on a thousand-word request (4,051 and 4,051 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.

Where it makes sense: 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, analysing a long document or codebase in one request.

Provider's own description

Aion 3.5 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...

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 out2,389 toman
Summarising a ten-page document4,000 in + 600 out5,401 toman
Classifying a thousand short rows120,000 in + 20,000 out166,185 toman

Frequently asked

How do I call Aion 3.5 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". Nothing else in your code changes.
What does Aion 3.5 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 3.5 take?
Up to 262,144 tokens per request, roughly 197k words. A single answer can reach 32,768 tokens.
Does Aion 3.5 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.