Xing4.0 29B A4B (free) API: toman pricing and code

xingchen-agi/xing4.0-29b-a4b:free

Free · shared capacityTool callingReasoningJSON output
Input · per 1M tokens
0 toman
Output · per 1M tokens
0 toman
One 1,000-word request ≈
0 toman

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

Xing4.0 29B A4B (free) 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="xingchen-agi/xing4.0-29b-a4b:free", 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="xingchen-agi/xing4.0-29b-a4b:free", messages=messages, tools=tools)
print(final.choices[0].message.content)
import OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.uttapen.ir/v1", apiKey: "sk-up-…" });

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

const messages = [{ role: "user", content: "How many of the Nike NK-42 shoe are in stock?" }];
const first = await client.chat.completions.create({ model: "xingchen-agi/xing4.0-29b-a4b:free", messages, tools });
const call = first.choices[0].message.tool_calls[0];

const args = JSON.parse(call.function.arguments);
const result = { sku: args.sku, qty: 7 };

messages.push(first.choices[0].message, { role: "tool", tool_call_id: call.id, content: JSON.stringify(result) });
const final = await client.chat.completions.create({ model: "xingchen-agi/xing4.0-29b-a4b:free", messages, tools });
console.log(final.choices[0].message.content);
curl https://api.uttapen.ir/v1/chat/completions \
  -H "Authorization: Bearer sk-up-…" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "xingchen-agi/xing4.0-29b-a4b:free",
    "messages": [{"role": "user", "content": "How many of the Nike NK-42 shoe are in stock?"}],
    "tools": [{
      "type": "function",
      "function": {
        "name": "check_stock",
        "parameters": {"type": "object", "properties": {"sku": {"type": "string"}}, "required": ["sku"]}
      }
    }]
  }'

What is Xing4.0 29B A4B (free) good for?

The id for Xing4.0 29B A4B (free) in our API is "xingchen-agi/xing4.0-29b-a4b:free", served from Xingchen Agi. Context is 262,144 tokens; past that you have to summarise the history yourself. A single response can run to 235,929 tokens. Using it costs nothing. In exchange the capacity is shared, so during busy hours a request can come back empty-handed.

Capabilities available on this id: 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 0 toman per 1,000-word exchange (0 in, 0 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 North Mini Code (free), 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.

Among the less common parameters it accepts min_p, presence_penalty, repetition_penalty, top_k — all through the standard request body. By context size the nearest option from another provider is Aion 3.5 at 262,144 tokens.

What to use it for: proving an idea works before you spend anything, logic puzzles and code review, 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

Xing4.0-29B-A4B is an open-weight mixture-of-experts language model from China Telecom's AI team (TeleAI) and the successor to the TeleChat series. It has 29B total parameters with 4B active per token...

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 out0 toman
Summarising a ten-page document4,000 in + 600 out0 toman
Classifying a thousand short rows120,000 in + 20,000 out0 toman

Frequently asked

How do I call Xing4.0 29B A4B (free) 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 "xingchen-agi/xing4.0-29b-a4b:free". Nothing else in your code changes.
What does Xing4.0 29B A4B (free) cost in toman?
0 toman per 1M input tokens and 0 toman per 1M output tokens; a 1,000-word request is around 0 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
How much input does Xing4.0 29B A4B (free) take?
Up to 262,144 tokens per request, roughly 197k words. A single answer can reach 235,929 tokens.
Does Xing4.0 29B A4B (free) 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.
What are the limits on a free model?
Free models have a daily per-user cap and their capacity is shared with everyone else. When the shared pool is exhausted the request is refused with a clear error and your wallet is untouched.