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Seed-2.0-Mini API: toman pricing and code

bytedance-seed/seed-2.0-mini

Image inputTool callingReasoningJSON output
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Input · per 1M tokens
34,622 toman
Output · per 1M tokens
138,488 toman
One 1,000-word request ≈
225 toman

You are billed for the usage the request actually reported. Prices follow the market.Pricing and top-ups

Seed-2.0-Mini 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.

# 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": "bytedance-seed/seed-2.0-mini",
    "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="bytedance-seed/seed-2.0-mini",
    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: "bytedance-seed/seed-2.0-mini",
  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 Seed-2.0-Mini good for?

ByteDance Seed publishes this model; we expose it under the id "bytedance-seed/seed-2.0-mini". Its context window is 262,144 tokens, roughly 197k English words in one request. A single response can run to 131,072 tokens. On price it sits in the "very cheap" band — cheaper than 317 and dearer than 74 of the other paid models in the catalogue.

Capabilities available on this id: it reads images directly, which makes it a real option for invoices, forms and screenshots; 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 225 toman per 1,000-word exchange (34,622 in, 138,488 out, per 1M tokens). 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 2.5 Flash Lite, and Seed-2.0-Mini costs about the same, 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 444 thousand-word requests on Seed-2.0-Mini, and every 1,000 toman is about 4,444 words of round trip. A job with one million input tokens and one million output tokens comes to 173,110 toman in total. Filling this model's 262,144-token window costs 9,076 toman on the input side alone, which is the real reason to keep conversation history short.

Its nearest relative in the catalogue is "bytedance-seed/seed-1.6-flash", and choosing between those two is where most people hesitate. On a thousand-word request this variant works out about 30% more expensive (225 against 169 toman). Maximum answer length differs as well: 131,072 against 32,768 tokens. On parameters, this one takes reasoning_effort.

ByteDance Seed has 6 models in our catalogue; the cheapest is Seed 1.6 Flash at 169 toman per thousand words and the dearest Seed-2.0-Code at 1,575. Among the less common parameters it accepts reasoning_effort — all through the standard request body. It does not support seed, 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 3.5 at 262,144 tokens.

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

Seed-2.0-mini targets latency-sensitive, high-concurrency, and cost-sensitive scenarios, emphasizing fast response and flexible inference deployment. It delivers performance comparable to ByteDance-Seed-1.6, supports 256k context, four reasoning effort modes (minimal/low/medium/high), multimodal understanding,...

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 out107 toman
Summarising a ten-page document4,000 in + 600 out222 toman
Classifying a thousand short rows120,000 in + 20,000 out6,924 toman

Frequently asked

How do I call Seed-2.0-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 "bytedance-seed/seed-2.0-mini". Nothing else in your code changes.
What does Seed-2.0-Mini cost in toman?
34,622 toman per 1M input tokens and 138,488 toman per 1M output tokens; a 1,000-word request is around 225 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
How much input does Seed-2.0-Mini take?
Up to 262,144 tokens per request, roughly 197k words. A single answer can reach 131,072 tokens.
Does Seed-2.0-Mini 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.