Cydonia 24B V4.1 API: toman pricing and code
thedrummer/cydonia-24b-v4.1
You are billed for the usage the request actually reported. Prices follow the market. Cached input: 51,933 toman per 1M tokens.Pricing and top-ups
Cydonia 24B V4.1 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="thedrummer/cydonia-24b-v4.1",
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: "thedrummer/cydonia-24b-v4.1",
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": "thedrummer/cydonia-24b-v4.1",
"messages": [{"role": "user", "content": "Classify the ticket and give it a priority from 1 to 5."}],
"response_format": {"type": "json_object"}
}'What is Cydonia 24B V4.1 good for?
Thedrummer publishes this model; we expose it under the id "thedrummer/
What you get on top of text in, text out: 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 103,866 toman per 1M tokens and output at 173,110 — output costs 1.7× input, so trimming the answer saves more than trimming the prompt. It supports cached input: repeated context is billed at 51,933 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 Hunyuan A13B Instruct: Cydonia 24B V4.1 works out about 10% more expensive, and its context window is the same size. 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 278 thousand-word requests on Cydonia 24B V4.1, and every 1,000 toman is about 2,778 words of round trip. A job with one million input tokens and one million output tokens comes to 276,975 toman in total. Filling this model's 131,072-token window costs 13,614 toman on the input side alone, which is the real reason to keep conversation history short.
Its nearest relative in the catalogue is "thedrummer/
Thedrummer has 3 models in our catalogue; the cheapest is Cydonia 24B V4.1 at 360 toman per thousand words and the dearest Skyfall 36B V2 at 608. Among the less common parameters it accepts logit_bias, logprobs, presence_penalty, repetition_penalty, top_k, top_logprobs — all through the standard request body. It does not support include_reasoning, reasoning, tool_choice, tools, 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-2.0 at 131,072 tokens.
Where it makes sense: high-volume work such as classification, tagging and bulk summarising, extracting data against a fixed schema.
Uncensored and creative writing model based on Mistral Small 3.2 24B with good recall, prompt adherence, and intelligence.
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 | 225 toman |
| Summarising a ten-page document | 4,000 in + 600 out | 519 toman |
| Classifying a thousand short rows | 120,000 in + 20,000 out | 15,926 toman |
Frequently asked
- How do I call Cydonia 24B V4.1 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 "thedrummer/ cydonia-24b-v4.1". Nothing else in your code changes. - What does Cydonia 24B V4.1 cost in toman?
- 103,866 toman per 1M input tokens and 173,110 toman per 1M output tokens; a 1,000-word request is around 360 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
- How much input does Cydonia 24B V4.1 take?
- Up to 131,072 tokens per request, roughly 98k words. A single answer can reach 117,964 tokens.
- Can I stream Cydonia 24B V4.1'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.