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Step 5 Preview API: toman pricing and code

stepfun/step-5-preview

Image inputTool callingReasoningJSON output
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Input · per 1M tokens
346,219 toman
Output · per 1M tokens
934,792 toman
One 1,000-word request ≈
1,665 toman

You are billed for the usage the request actually reported. Prices follow the market. Cached input: 34,622 toman per 1M tokens.Pricing and top-ups

Step 5 Preview 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": "stepfun/step-5-preview",
    "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="stepfun/step-5-preview",
    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: "stepfun/step-5-preview",
  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 Step 5 Preview good for?

Step 5 Preview comes from StepFun; in uttapen you reach it with the model id "stepfun/step-5-preview". It accepts up to 1,048,576 tokens of input per call, so a long document or several source files fit in a single request. A single response can run to 64,000 tokens. On price it sits in the "mid-range" band — cheaper than 156 and dearer than 241 of the other paid models in the catalogue.

What it can do beyond plain text: 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.

Pricing is 346,219 toman per 1M input tokens and 934,792 per 1M output tokens. A 1,000-word round trip on Step 5 Preview lands near 1,665 toman. It supports cached input: repeated context is billed at 34,622 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 Qwen3.6 27B: Step 5 Preview works out about 20% more expensive, 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 60 thousand-word requests on Step 5 Preview, and every 1,000 toman is about 601 words of round trip. A job with one million input tokens and one million output tokens comes to 1,281,012 toman in total. Filling this model's 1,048,576-token window costs 363,037 toman on the input side alone, which is the real reason to keep conversation history short.

Its nearest relative in the catalogue is "stepfun/step-3.7-flash", and choosing between those two is where most people hesitate. On a thousand-word request this variant works out about 2.7× more expensive (1,665 against 608 toman). The context windows differ too: 1,048,576 against 262,144 tokens. Maximum answer length differs as well: 64,000 against 230,400 tokens. On parameters, this one takes min_p.

StepFun has 3 models in our catalogue; the cheapest is Step 3.5 Flash at 180 toman per thousand words and the dearest Step 5 Preview at 1,665. Among the less common parameters it accepts logprobs, min_p, presence_penalty, reasoning_effort, repetition_penalty, top_k — all through the standard request body. By context size the nearest option from another provider is DeepSeek V4 Flash 0423 at 1,048,576 tokens.

Good fits: 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

Step 5 Preview is StepFun's flagship model for agentic work, built on a sparse Mixture-of-Experts architecture (27B active / 600B total parameters). It performs strongly in software engineering and professional...

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 out893 toman
Summarising a ten-page document4,000 in + 600 out1,946 toman
Classifying a thousand short rows120,000 in + 20,000 out60,242 toman

Price history

DateInput (toman/1M)Output (toman/1M)
16 Oct 2026346,219934,792
8 Oct 2026346,219934,792

Every price change for this model is recorded. Toman figures use today's rate.

Frequently asked

How do I call Step 5 Preview 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 "stepfun/step-5-preview". Nothing else in your code changes.
What does Step 5 Preview cost in toman?
346,219 toman per 1M input tokens and 934,792 toman per 1M output tokens; a 1,000-word request is around 1,665 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
How much input does Step 5 Preview take?
Up to 1,048,576 tokens per request, roughly 786k words. A single answer can reach 64,000 tokens.
Does Step 5 Preview 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.