Seed-2.0-Code API: toman pricing and code
bytedance-seed/seed-2.0-code
visiontoolsreasoningjsonYou are billed for the usage the request actually reported. Prices follow the market.Pricing and top-ups
Seed-2.0-Code 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-code",
"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-code",
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-code",
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-Code good for?
Seed-2.0-Code is one of ByteDance Seed's models. Put "bytedance-seed/seed-2.0-code" in the model field and the rest of your code stays as it is. Seed-2.0-Code keeps 262,144 tokens in view at once, and that number is what caps the conversation history in your product. A single response can run to 131,072 tokens. On price it sits in the "mid-range" band — cheaper than 242 and dearer than 164 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 145,063 toman per 1M tokens and output at 870,375 — output costs 6× 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 Gemini 3 Flash Preview: Seed-2.0-Code works out roughly 1× 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 76 thousand-word requests on Seed-2.0-Code, and every 1,000 toman is about 758 words of round trip. A job with one million input tokens and one million output tokens comes to 1,015,438 toman in total. Filling this model's 262,144-token window costs 38,027 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-2-1-turbo", and choosing between those two is where most people hesitate. On a thousand-word request this variant works out 1.2× dearer (1,320 against 1,131 toman). Maximum answer length differs as well: 131,072 against 235,929 tokens. On parameters, this one takes reasoning_effort.
ByteDance Seed has 6 models in our catalogue; the cheapest is Seed 1.6 Flash at 141 toman per thousand words and the dearest Seed-2.0-Code at 1,320. 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 Trinity Large Thinking 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.
Seed 2.0 Code is a model from ByteDance Seed optimized for agentic coding. It is suited for frontend development, multilingual programming tasks, and coding-agent workflows in tools such as Claude...
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 | 566 toman |
| Summarising a ten-page document | 4,000 in + 600 out | 1,102 toman |
| Classifying a thousand short rows | 120,000 in + 20,000 out | 34,815 toman |
Frequently asked
- How do I call Seed-2.0-Code 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-code". Nothing else in your code changes.
- What does Seed-2.0-Code cost in toman?
- 145,063 toman per 1M input tokens and 870,375 toman per 1M output tokens; a 1,000-word request is around 1,320 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
- How much input does Seed-2.0-Code take?
- Up to 262,144 tokens per request, roughly 197k words. A single answer can reach 131,072 tokens.
- Does Seed-2.0-Code 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.