How much does MiniMax M2 cost?

MiniMax M2 is billed per generation rather than per token. See the pricing page for the current rate.

What is the context window of MiniMax M2?

MiniMax M2 supports a context window of up to 205K tokens. It can return up to 131K tokens in a single response.

What can MiniMax M2 do?

MiniMax M2 supports Tool calling, Reasoning.

Is MiniMax M2 free to use?

MiniMax M2 is a paid, pay-as-you-go model — no subscription, you are only charged for usage.

How do I use MiniMax M2 via the API?

MiniMax M2 is OpenAI-compatible. Point any OpenAI SDK at https://api.airforce/v1 and pass the model ID minimax-m2 with your Api.Airforce API key.

Who makes MiniMax M2?

MiniMax M2 is MiniMax's chat model, served through the unified Api.Airforce gateway alongside 100+ other models.

MiniMaxPaidOperational

MiniMax M2

API model name: minimax-m2

MiniMax M2 is MiniMax's chat model, served on the Api.Airforce unified API. It has a 205K-token context window. Capabilities include Tool calling, Reasoning. Access it through the OpenAI-compatible API with one key, alongside 100+ other models on Api.Airforce.

Get an API key View pricing

Pricing

Input / 1M tokens

—

Output / 1M tokens

—

Specifications

Provider: MiniMax
Type: chat model
Context window: 205K tokens
Max output: 131K tokens
Input: text
Output: text

Capabilities

Tool callingReasoningStreaming

Benchmarks

Independent evaluations and measured speed from Artificial Analysis.

Intelligence Index

28.3/100

Math Index

78.3/100

MMLU-Pro82%

GPQA Diamond78%

Humanity's Last Exam13%

LiveCodeBench83%

AIME 202578%

Output speed114.0 tok/s

Time to first token0.95 s

Source: Benchmark data by Artificial Analysis (artificialanalysis.ai)

What is MiniMax M2 used for?

Chatbots & assistants — conversational AI, drafting, summarizing and Q&A.
Agents & automation — function calling and tool use for multi-step workflows.
Complex reasoning — math, coding and step-by-step problem solving.
Long-context tasks — process entire documents or codebases in a single prompt.
Real-time experiences — stream tokens for responsive chat and apps.

MiniMax M2 vs. similar models

Model	Intelligence	Context	Input / 1M	Output / 1M
MiniMax M2	28.3	205K	—	—
MiniMax M2.1	31.4	—	$0.90	$3.66
MiniMax M2.5	33.7	246K	Free	Free
MiniMax M2.7	38.1	—	$4.50	$18.00

Prices are Api.Airforce pay-as-you-go rates per 1M tokens. Context is the maximum input length.

MiniMax M2 — frequently asked questions

How much does MiniMax M2 cost?: MiniMax M2 is billed per generation rather than per token. See the pricing page for the current rate.
What is the context window of MiniMax M2?: MiniMax M2 supports a context window of up to 205K tokens. It can return up to 131K tokens in a single response.
What can MiniMax M2 do?: MiniMax M2 supports Tool calling, Reasoning.
Is MiniMax M2 free to use?: MiniMax M2 is a paid, pay-as-you-go model — no subscription, you are only charged for usage.
How do I use MiniMax M2 via the API?: MiniMax M2 is OpenAI-compatible. Point any OpenAI SDK at https://api.airforce/v1 and pass the model ID minimax-m2 with your Api.Airforce API key.
Who makes MiniMax M2?: MiniMax M2 is MiniMax's chat model, served through the unified Api.Airforce gateway alongside 100+ other models.

All models·Quickstart·Chat API reference

Use MiniMax M2 via the API

OpenAI-compatible — point any OpenAI SDK at https://api.airforce/v1 and pass minimax-m2 as the model.

cURL

curl https://api.airforce/v1/chat/completions \
  -H "Authorization: Bearer $AIRFORCE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "minimax-m2",
    "messages": [{ "role": "user", "content": "Hello!" }]
  }'

Python

from openai import OpenAI
client = OpenAI(base_url="https://api.airforce/v1", api_key="$AIRFORCE_API_KEY")
r = client.chat.completions.create(
    model="minimax-m2",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(r.choices[0].message.content)

JavaScript

import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://api.airforce/v1", apiKey: process.env.AIRFORCE_API_KEY });
const r = await client.chat.completions.create({
  model: "minimax-m2",
  messages: [{ role: "user", content: "Hello!" }],
});
console.log(r.choices[0].message.content);