How do I call MiniMax M1 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 "minimax/minimax-m1". Nothing else in your code changes.

What does MiniMax M1 cost in toman?

190,421 toman per 1M input tokens and 761,683 toman per 1M output tokens; a 1,000-word request is around 1,238 toman. You pay for the usage that request actually reported, and a failed request costs nothing.

How much input does MiniMax M1 take?

Up to 1,000,000 tokens per request, roughly 750k words. A single answer can reach 40,000 tokens.

Does MiniMax M1 support streaming and tool calling?

Streaming (stream=true) works on every model here. This one supports tool calling in the standard OpenAI shape.

MiniMax M1 API: toman pricing and code

minimax/minimax-m1

Tool callingReasoning

Create a key Try it

Input · per 1M tokens

190,421 toman

Output · per 1M tokens

761,683 toman

One 1,000-word request ≈

1,238 toman

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

MiniMax M1 example: a multi-step problem with reasoning

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

PythoncurlNode.js

from openai import OpenAI

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

resp = client.chat.completions.create(
    model="minimax/minimax-m1",
    messages=[{"role": "user", "content": (
        "A shop has 3 warehouses. A ships 120 orders a day, B ships 85 and C ships 40. "
        "If C closes and its load is split between A and B in proportion to their capacity, how many does each ship a day? "
        "Work through it step by step and give just the two numbers at the end."
    )}],
    reasoning_effort="medium",   # low | medium | high
)
print(resp.choices[0].message.content)
# reasoning tokens count as output tokens too:
print(resp.usage.completion_tokens_details)

curl https://api.uttapen.ir/v1/chat/completions \
  -H "Authorization: Bearer sk-up-…" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "minimax/minimax-m1",
    "messages": [{"role": "user", "content": "120 and 85 daily orders split across two warehouses; work through it step by step."}],
    "reasoning": {"effort": "medium"}
  }'

import OpenAI from "openai";

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

const resp = await client.chat.completions.create({
  model: "minimax/minimax-m1",
  messages: [{ role: "user", content: "120 and 85 daily orders are split between two warehouses; work through it step by step and give just the two numbers at the end." }],
  reasoning_effort: "medium",
});
console.log(resp.choices[0].message.content);
console.log(resp.usage.completion_tokens_details);

What is MiniMax M1 good for?

MiniMax M1 is one of MiniMax's models. Put "minimax/minimax-m1" in the model field and the rest of your code stays as it is. MiniMax M1 keeps 1,000,000 tokens in view at once, and that number is what caps the conversation history in your product. A single response can run to 40,000 tokens. On price it sits in the "mid-range" band — cheaper than 179 and dearer than 217 of the other paid models in the catalogue.

Capabilities available on this id: it supports tool calling, so it can invoke your own functions with valid arguments; 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 1,238 toman per 1,000-word exchange (190,421 in, 761,683 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 GLM 4.5, and MiniMax M1 costs about the same, 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 81 thousand-word requests on MiniMax M1, and every 1,000 toman is about 808 words of round trip. A job with one million input tokens and one million output tokens comes to 952,103 toman in total. Filling this model's 1,000,000-token window costs 190,421 toman on the input side alone, which is the real reason to keep conversation history short.

Its nearest relative in the catalogue is "minimax/minimax-m2", and choosing between those two is where most people hesitate. On a thousand-word request this variant works out about 2.2× more expensive (1,238 against 574 toman). The context windows differ too: 1,000,000 against 204,800 tokens. Maximum answer length differs as well: 40,000 against 131,072 tokens. On parameters, this one takes frequency_penalty, presence_penalty, repetition_penalty, seed.

MiniMax has 9 models in our catalogue; the cheapest is MiniMax M3.1 Flash at 338 toman per thousand words and the dearest MiniMax M1 at 1,238. Among the less common parameters it accepts presence_penalty, repetition_penalty, top_k — all through the standard request body. It does not support response_format, structured_outputs, 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 Nova 2 Lite at 1,000,000 tokens.

What to use it for: product chatbots and internal assistants, where cost and quality have to balance, logic puzzles and code review, agents that reach out to APIs and databases, analysing a long document or codebase in one request.

Provider's own description

MiniMax-M1 is a large-scale, open-weight reasoning model designed for extended context and high-efficiency inference. It leverages a hybrid Mixture-of-Experts (MoE) architecture paired with a custom "lightning attention" mechanism, allowing it...

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	590 toman
Summarising a ten-page document	4,000 in + 600 out	1,219 toman
Classifying a thousand short rows	120,000 in + 20,000 out	38,084 toman

Job

Tokens

Cost

One chat turn with a medium history

1,500 in + 400 out

590 toman

Summarising a ten-page document

4,000 in + 600 out

1,219 toman

Classifying a thousand short rows

120,000 in + 20,000 out

38,084 toman

Price history

Date	Input (toman/1M)	Output (toman/1M)
1 Oct 2026	190,421	761,683
16 Sep 2026	138,488	761,683
9 Sep 2026	190,421	761,683
8 Sep 2026	138,488	761,683
8 Sep 2026	190,421	761,683
8 Sep 2026	138,488	761,683
7 Sep 2026	190,421	761,683

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

Frequently asked

How do I call MiniMax M1 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 "minimax/minimax-m1". Nothing else in your code changes.
What does MiniMax M1 cost in toman?: 190,421 toman per 1M input tokens and 761,683 toman per 1M output tokens; a 1,000-word request is around 1,238 toman. You pay for the usage that request actually reported, and a failed request costs nothing.
How much input does MiniMax M1 take?: Up to 1,000,000 tokens per request, roughly 750k words. A single answer can reach 40,000 tokens.
Does MiniMax M1 support streaming and tool calling?: Streaming (stream=true) works on every model here. This one supports tool calling in the standard OpenAI shape.