MiMo-V2.5-Pro API: toman pricing and code
xiaomi/mimo-v2.5-pro
You are billed for the usage the request actually reported. Prices follow the market. Cached input: 33,237 toman per 1M tokens.Pricing and top-ups
MiMo-V2.5-Pro 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="xiaomi/mimo-v2.5-pro", 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="xiaomi/mimo-v2.5-pro", 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: "xiaomi/mimo-v2.5-pro", 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: "xiaomi/mimo-v2.5-pro", 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": "xiaomi/mimo-v2.5-pro",
"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 MiMo-V2.5-Pro good for?
MiMo-V2.5-Pro is one of Xiaomi's models. Put "xiaomi/
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 1,026 toman per 1,000-word exchange (166,185 in, 623,195 out, per 1M tokens). It supports cached input: repeated context is billed at 33,237 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 Aion-2.0: MiMo-V2.5-Pro 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 97 thousand-word requests on MiMo-V2.5-Pro, and every 1,000 toman is about 975 words of round trip. A job with one million input tokens and one million output tokens comes to 789,380 toman in total. Filling this model's 1,050,000-token window costs 174,495 toman on the input side alone, which is the real reason to keep conversation history short.
Xiaomi has 5 models in our catalogue; the cheapest is MiMo-V2.6-Flash at 189 toman per thousand words and the dearest MiMo-V2.6-Pro-UltraSpeed at 5,874. Among the less common parameters it accepts logprobs, top_logprobs — all through the standard request body. By context size the nearest option from another provider is GPT-5.4 at 1,050,000 tokens.
What to use it for: high-volume work such as classification, tagging and bulk summarising, 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.
MiMo-V2.5-Pro is Xiaomi’s flagship model, delivering strong performance in general agentic capabilities, complex software engineering, and long-horizon tasks, with top rankings on benchmarks such as ClawEval, GDPVal, and SWE-bench Pro....
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 | 499 toman |
| Summarising a ten-page document | 4,000 in + 600 out | 1,039 toman |
| Classifying a thousand short rows | 120,000 in + 20,000 out | 32,406 toman |
Price history
| Date | Input (toman/1M) | Output (toman/1M) |
|---|---|---|
| 27 Oct 2026 | 166,185 | 623,195 |
| 21 Oct 2026 | 105,424 | 210,848 |
| 7 Sep 2026 | 150,605 | 301,211 |
Every price change for this model is recorded. Toman figures use today's rate.
Frequently asked
- How do I call MiMo-V2.5-Pro 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 "xiaomi/ mimo-v2.5-pro". Nothing else in your code changes. - What does MiMo-V2.5-Pro cost in toman?
- 166,185 toman per 1M input tokens and 623,195 toman per 1M output tokens; a 1,000-word request is around 1,026 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
- How much input does MiMo-V2.5-Pro take?
- Up to 1,050,000 tokens per request, roughly 788k words. A single answer can reach 235,929 tokens.
- Does MiMo-V2.5-Pro 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.