Minimax M3 API 多少錢?

WaveSpeedAI 定價:輸入每百萬 token $0.60,輸出每百萬 token $2.40。Prompt 快取與批次處理分別計費,可顯著降低長上下文、高重複任務的實際成本。

Minimax M3 的上下文視窗有多大?

Minimax M3 每次請求最多支援 1049K 上下文 token,輸出最多 512K token。

Minimax M3 是否相容 OpenAI?

WaveSpeedAI 透過 https://llm.wavespeed.ai/v1 的 OpenAI 相容 Chat Completions 介面提供 Minimax M3。大多數 OpenAI SDK 用戶端只需更換 base URL 和 API Key；選用欄位取決於具體模型。

如何開始使用 Minimax M3?

登入 WaveSpeedAI，在 Access Keys 中建立 API Key，然後使用上方顯示的 model id 向 https://llm.wavespeed.ai/v1/chat/completions 發送請求。模型可用性、能力和價格請以目前模型目錄為準。

MiniMax M3 | Minimax Multimodal LLM API Pricing

Name: Minimax M3 API
Brand: minimax
Price: 0.6 USD
Availability: InStock

minimax/minimax-m3

發布時間: 2026-06-01

1,048,576 context · $0.60/M input tokens · $2.40/M output tokens

MiniMax-M3 is MiniMax’s latest M-series multimodal foundation model for agent reasoning, tool use, coding, and long-context tasks. It supports text, image, and video inputs with text output, a 1M-token context window, thinking content, function calling, and structured outputs. With support for long-horizon agentic work, coding workflows, multimodal understanding, and very long responses, MiniMax-M3 is well suited for building autonomous agents, code assistants, document/video analysis tools, and production workflows that need large context at efficient pricing.

定價

按用量付費

無需預付費用，僅按實際使用量付費

輸入

≤ 512K $0.60 / M Tokens

> 512K $1.20 / M Tokens

輸出

≤ 512K $2.40 / M Tokens

> 512K $4.80 / M Tokens

Cache Read

≤ 512K $0.12 / M Tokens

> 512K $0.24 / M Tokens

試用模型

minimax/minimax-m3

線上

嗨！我是樂於助人的 AI 助理。有什麼可以幫你的嗎？

準備在本機編碼 Agent 中使用這個模型嗎？Agent 設定

API 使用

使用以下程式碼範例整合我們的 API：

import OpenAI from 'openai';

if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
  apiKey: process.env.WAVESPEED_API_KEY,
  baseURL: 'https://llm.wavespeed.ai/v1',
  timeout: 120_000,
  maxRetries: 2,
});

try {
  const response = await client.chat.completions.create({
    model: 'minimax/minimax-m3',
    messages: [{ role: 'user', content: 'Hello!' }],
  });
  console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
  console.error('LLM request failed:', error);
  process.exitCode = 1;
}

import OpenAI from 'openai';

if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
  apiKey: process.env.WAVESPEED_API_KEY,
  baseURL: 'https://llm.wavespeed.ai/v1',
  timeout: 120_000,
  maxRetries: 2,
});

try {
  const response = await client.chat.completions.create({
    model: 'minimax/minimax-m3',
    messages: [{ role: 'user', content: 'Hello!' }],
  });
  console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
  console.error('LLM request failed:', error);
  process.exitCode = 1;
}

模型介紹

MiniMax: MiniMax M3

Why It Looks Great

Latest MiniMax M-series language model for agent reasoning, tools, coding, and long-context work
Native multimodal support for text, image, and video understanding
1M-token context window for long prompts, large documents, videos, codebases, and multi-turn workflows
Up to 512K output tokens for unusually long responses, extended reasoning, and structured generation
Strong fit for long-horizon agentic work, coding workflows, document analysis, and multimodal assistants
Thinking content support for transparent multi-step reasoning workflows
Function calling and tool-use support for agentic application workflows
Structured output support for JSON responses and schema-constrained generation
Efficient pricing for large-context multimodal production use cases

Key Features

Context Window: 1,048,576 tokens
Max Input: 536,576 tokens
Max Output: 512,000 tokens
Input: Text, Image, Video
Output: Text
Vision: Supported
Video Input: Supported
Function Calling: Supported
Structured Outputs: Supported
Thinking Mode: Supported
Image Generation: Not listed
Audio Input: Not listed
Supported Parameters: include_reasoning, max_tokens, reasoning, response_format, temperature, tool_choice, tools, top_p

Specifications

Specification	Value
Provider	minimax
Model Type	Chat Completions model
Architecture	text+image+video->text
Context Window	1,048,576 tokens
Max Input	536,576 tokens
Max Output	512,000 tokens
Input	Text, Image, Video
Output	Text
Vision	Supported
Video Input	Supported
Function Calling	Supported
Structured Outputs	Supported
Thinking Mode	Supported

How to Use

Write your prompt - describe the task, provide context, and specify the desired output format.
Submit - the model processes your request and returns the response.

API Integration

Base URL: https://llm.wavespeed.ai/v1
API Endpoint: chat/completions
Model ID: minimax/minimax-m3

API Usage

Python SDK

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

response = client.chat.completions.create(
    model="minimax/minimax-m3",
    messages=[{"role": "user", "content": "Hello!"}]
)

print(response.choices[0].message.content)

cURL

curl https://llm.wavespeed.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "minimax/minimax-m3",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

Model: minimax/minimax-m3
Provider: minimax
Best suited for long-horizon agents, coding, tool use, long-context document analysis, multimodal understanding, and structured output workflows
Image input supports common image formats such as JPEG, PNG, GIF, and WEBP
Video input is supported through URL, base64, or uploaded file references where available

資訊

提供商minimax

類型llm

支援功能

輸入

文字影像

輸出

文字

上下文1,048,576

最大輸出512,000

視覺✓ 支援

函式呼叫✓ 支援

API 存取指南

Base URLhttps://llm.wavespeed.ai/v1

API 端點chat/completions

Model IDminimax/minimax-m3

定價