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KAT-Coder-Pro V2.5 API: toman pricing and code

kwaipilot/kat-coder-pro-v2.5

toolsjson
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Input · per 1M tokens
214,693 toman
Output · per 1M tokens
858,770 toman
One 1,000-word request ≈
1,396 toman

You are billed for the usage the request actually reported. Prices follow the market. Cached input: 43,519 toman / 1M.Pricing and top-ups

KAT-Coder-Pro V2.5 example: tool calling

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

from openai import OpenAI
import json

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

tools = [{
    "type": "function",
    "function": {
        "name": "check_stock",
        "description": "Returns the stock level of a product",
        "parameters": {
            "type": "object",
            "properties": {"sku": {"type": "string"}},
            "required": ["sku"],
        },
    },
}]

messages = [{"role": "user", "content": "How many of the Nike NK-42 shoe are in stock?"}]
first = client.chat.completions.create(model="kwaipilot/kat-coder-pro-v2.5", messages=messages, tools=tools)
call = first.choices[0].message.tool_calls[0]

# you run the function yourself — the model never touches the database
args = json.loads(call.function.arguments)
result = {"sku": args["sku"], "qty": 7}

messages += [first.choices[0].message, {"role": "tool", "tool_call_id": call.id, "content": json.dumps(result)}]
final = client.chat.completions.create(model="kwaipilot/kat-coder-pro-v2.5", messages=messages, tools=tools)
print(final.choices[0].message.content)

What is KAT-Coder-Pro V2.5 good for?

The id for KAT-Coder-Pro V2.5 in our API is "kwaipilot/kat-coder-pro-v2.5", served from Kwaipilot. Context is 262,144 tokens; past that you have to summarise the history yourself. A single response can run to 235,929 tokens. On price it sits in the "mid-range" band — cheaper than 241 and dearer than 165 of the other paid models in the catalogue.

What you get on top of text in, text out: 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. All of it works through the standard parameters of the official OpenAI SDK — no custom client, no wrapper.

Input runs at 214,693 toman per 1M tokens and output at 858,770 — output costs 4× input, so trimming the answer saves more than trimming the prompt. It supports cached input: repeated context is billed at 43,519 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 Relace Search: KAT-Coder-Pro V2.5 works out roughly 1.1× 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 72 thousand-word requests on KAT-Coder-Pro V2.5, and every 1,000 toman is about 716 words of round trip. A job with one million input tokens and one million output tokens comes to 1,073,463 toman in total. Filling this model's 262,144-token window costs 56,280 toman on the input side alone, which is the real reason to keep conversation history short.

Its nearest relative in the catalogue is "kwaipilot/kat-coder-pro-v2", and choosing between those two is where most people hesitate. On a thousand-word request this variant works out 2.5× dearer (1,396 against 566 toman). Maximum answer length differs as well: 235,929 against 144,000 tokens.

Kwaipilot has 2 models in our catalogue; the cheapest is KAT-Coder-Pro V2 at 566 toman per thousand words and the dearest KAT-Coder-Pro V2.5 at 1,396. Among the less common parameters it accepts logit_bias, min_p, repetition_penalty, top_k — all through the standard request body. It does not support include_reasoning, reasoning, 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, 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

KAT-Coder-Pro V2.5 is a flagship-level Agentic Coding model that can directly hand over an entire issue or an entire business workflow to it, allowing it to autonomously locate and make...

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 out666 toman
Summarising a ten-page document4,000 in + 600 out1,374 toman
Classifying a thousand short rows120,000 in + 20,000 out42,939 toman

Frequently asked

How do I call KAT-Coder-Pro V2.5 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 "kwaipilot/kat-coder-pro-v2.5". Nothing else in your code changes.
What does KAT-Coder-Pro V2.5 cost in toman?
214,693 toman per 1M input tokens and 858,770 toman per 1M output tokens; a 1,000-word request is around 1,396 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
How much input does KAT-Coder-Pro V2.5 take?
Up to 262,144 tokens per request, roughly 197k words. A single answer can reach 235,929 tokens.
Does KAT-Coder-Pro V2.5 support streaming and tool calling?
Streaming (stream=true) works on every model here. This one supports tool calling in the standard OpenAI shape. Structured output through response_format works too.