How do I call Fugu Max 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 "sakana/fugu-max". Nothing else in your code changes.

What does Fugu Max cost in toman?

692,439 toman per 1M input tokens and 2,077,316 toman per 1M output tokens; a 1,000-word request is around 3,601 toman. You pay for the usage that request actually reported, and a failed request costs nothing.

How much input does Fugu Max take?

Up to 1,000,000 tokens per request, roughly 750k words. A single answer can reach 128,000 tokens.

Does Fugu Max support streaming and tool calling?

Streaming (stream=true) works on every model here. This one supports tool calling in the standard OpenAI shape. Image input is accepted through image_url, as a data URI or a public URL. Structured output through response_format works too.

Fugu Max API: toman pricing and code

sakana/fugu-max

Image inputTool callingReasoningJSON outputFile input

Create a key Try it

Input · per 1M tokens

692,439 toman

Output · per 1M tokens

2,077,316 toman

One 1,000-word request ≈

3,601 toman

You are billed for the usage the request actually reported. Prices follow the market. Cached input: 86,555 toman per 1M tokens. Web search: 3,462.19 toman per request.Pricing and top-ups

Fugu Max example: reading an image into JSON

The example is picked from this model's own capabilities. Drop in your key and it runs as is.

curlPythonNode.js

# tip: a data URI works too — base64 the file and prefix it with data:image/jpeg;base64,
curl https://api.uttapen.ir/v1/chat/completions \
  -H "Authorization: Bearer sk-up-…" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "sakana/fugu-max",
    "messages": [{
      "role": "user",
      "content": [
        {"type": "text", "text": "Return only the invoice number and the total, as JSON."},
        {"type": "image_url", "image_url": {"url": "https://example.com/factor.jpg"}}
      ]
    }]
  }'

import base64, json
from openai import OpenAI

client = OpenAI(base_url="https://api.uttapen.ir/v1", api_key="sk-up-…")

img = base64.b64encode(open("factor.jpg", "rb").read()).decode()

resp = client.chat.completions.create(
    model="sakana/fugu-max",
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "Return the invoice number, the date and the total as JSON."},
            {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{img}"}},
        ],
    }],
    response_format={"type": "json_object"},
)
print(json.loads(resp.choices[0].message.content))

import OpenAI from "openai";
import { readFileSync } from "node:fs";

const client = new OpenAI({ baseURL: "https://api.uttapen.ir/v1", apiKey: "sk-up-…" });
const img = readFileSync("factor.jpg").toString("base64");

const resp = await client.chat.completions.create({
  model: "sakana/fugu-max",
  messages: [{
    role: "user",
    content: [
      { type: "text", text: "Return the invoice number, the date and the total as JSON." },
      { type: "image_url", image_url: { url: `data:image/jpeg;base64,${img}` } },
    ],
  }],
  response_format: { type: "json_object" },
});
console.log(JSON.parse(resp.choices[0].message.content));

What is Fugu Max good for?

Sakana publishes this model; we expose it under the id "sakana/fugu-max". Its context window is 1,000,000 tokens, roughly 750k English words in one request. A single response can run to 128,000 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 reads images directly, which makes it a real option for invoices, forms and screenshots; it takes files such as PDFs as input; 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 692,439 toman per 1M tokens and output at 2,077,316 — output costs 3× input, so trimming the answer saves more than trimming the prompt. It supports cached input: repeated context is billed at 86,555 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 Gemini 3.1 Pro Preview (batch): Fugu Max works out about 10% 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 28 thousand-word requests on Fugu Max, and every 1,000 toman is about 278 words of round trip. A job with one million input tokens and one million output tokens comes to 2,769,755 toman in total. Filling this model's 1,000,000-token window costs 692,439 toman on the input side alone, which is the real reason to keep conversation history short.

Its nearest relative in the catalogue is "sakana/fugu-ultra", and choosing between those two is where most people hesitate. On a thousand-word request this variant works out about 4.4× cheaper (3,601 against 15,753 toman).

Sakana has 3 models in our catalogue; the cheapest is Fugu Max at 3,601 toman per thousand words and the dearest Fugu Ultra v2 at 15,753. Among the less common parameters it accepts reasoning_effort, web_search_options — all through the standard request body. It does not support max_tokens, response_format, temperature, top_p, 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 Nova 2 Lite at 1,000,000 tokens.

Where it makes sense: product chatbots and internal assistants, where cost and quality have to balance, logic puzzles and code review, pulling text and fields out of images, 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

Fugu Max is the cost-performance model in Sakana AI's Fugu family. Rather than a single monolithic model, Fugu is a learned multi-agent orchestration system: a language model trained to route...

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	1,870 toman
Summarising a ten-page document	4,000 in + 600 out	4,016 toman
Classifying a thousand short rows	120,000 in + 20,000 out	124,639 toman

Job

Tokens

Cost

One chat turn with a medium history

1,500 in + 400 out

1,870 toman

Summarising a ten-page document

4,000 in + 600 out

4,016 toman

Classifying a thousand short rows

120,000 in + 20,000 out

124,639 toman

Frequently asked

How do I call Fugu Max 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 "sakana/fugu-max". Nothing else in your code changes.
What does Fugu Max cost in toman?: 692,439 toman per 1M input tokens and 2,077,316 toman per 1M output tokens; a 1,000-word request is around 3,601 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
How much input does Fugu Max take?: Up to 1,000,000 tokens per request, roughly 750k words. A single answer can reach 128,000 tokens.
Does Fugu Max support streaming and tool calling?: Streaming (stream=true) works on every model here. This one supports tool calling in the standard OpenAI shape. Image input is accepted through image_url, as a data URI or a public URL. Structured output through response_format works too.