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Seed-2.0-Lite API: toman pricing and code

bytedance-seed/seed-2.0-lite

Image inputTool callingReasoningJSON output
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Input · per 1M tokens
86,555 toman
Output · per 1M tokens
692,439 toman
One 1,000-word request ≈
1,013 toman

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

Seed-2.0-Lite 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-lite",
    "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-lite",
    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-lite",
  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-Lite good for?

Seed-2.0-Lite comes from ByteDance Seed; in uttapen you reach it with the model id "bytedance-seed/seed-2.0-lite". 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 131,072 tokens. On price it sits in the "mid-range" band — cheaper than 185 and dearer than 200 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 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 86,555 toman per 1M tokens and output at 692,439 — output costs 8× input, so trimming the answer saves more than trimming the prompt. 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 Medium 3: Seed-2.0-Lite works out about 9% cheaper, 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 99 thousand-word requests on Seed-2.0-Lite, and every 1,000 toman is about 987 words of round trip. A job with one million input tokens and one million output tokens comes to 778,994 toman in total. Filling this model's 262,144-token window costs 22,690 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", and choosing between those two is where most people hesitate. Both land at nearly the same price on a thousand-word request (1,013 and 1,013 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.

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

Seed-2.0-Lite is a versatile, cost‑efficient enterprise workhorse that delivers strong multimodal and agent capabilities while offering noticeably lower latency, making it a practical default choice for most production workloads across...

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 out407 toman
Summarising a ten-page document4,000 in + 600 out762 toman
Classifying a thousand short rows120,000 in + 20,000 out24,235 toman

Frequently asked

How do I call Seed-2.0-Lite 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-lite". Nothing else in your code changes.
What does Seed-2.0-Lite cost in toman?
86,555 toman per 1M input tokens and 692,439 toman per 1M output tokens; a 1,000-word request is around 1,013 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
How much input does Seed-2.0-Lite take?
Up to 262,144 tokens per request, roughly 197k words. A single answer can reach 131,072 tokens.
Does Seed-2.0-Lite 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.