Minimax M3 API 多少钱?

WaveSpeedAI 定价:输入每百万 token $0.60,输出每百万 token $2.40。Prompt 缓存和批处理单独计费,可显著降低长上下文、高重复任务的实际成本。

Minimax M3 的上下文窗口是多大?

Minimax M3 单次请求最多支持 1049K 上下文 token,输出最多 512K token。

Minimax M3 是否兼容 OpenAI?

WaveSpeedAI 通过 https://llm.wavespeed.ai/v1 的 OpenAI 兼容 Chat Completions 接口提供 Minimax M3。大多数 OpenAI SDK 客户端只需更换 base URL 和 API Key；可选字段取决于具体模型。

如何开始使用 Minimax M3?

登录 WaveSpeedAI，在 Access Keys 中创建 API Key，然后使用上方显示的 model id 向 https://llm.wavespeed.ai/v1/chat/completions 发送请求。模型可用性、能力和价格请以当前模型目录为准。

MiniMax M3 | Minimax Multimodal LLM API Pricing

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

minimax/minimax-m3

发布时间: 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.

定价

按量付费

无需预付费用，仅按实际使用量付费

输入

≤ 512K $0.60 / M Tokens

> 512K $1.20 / M Tokens

输出

≤ 512K $2.40 / M Tokens

> 512K $4.80 / M Tokens

Cache Read

≤ 512K $0.12 / M Tokens

> 512K $0.24 / M Tokens

试用模型

minimax/minimax-m3

在线

你好！我是乐于助人的 AI 助手。需要我帮你做什么？

准备在本地编码 Agent 中使用这个模型吗？Agent 配置

API 使用

使用以下代码示例接入我们的 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;
}

模型介绍

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

信息

提供商minimax

类型llm

支持功能

输入

文本图像

输出

文本

上下文1,048,576

最大输出512,000

视觉✓ 支持

函数调用✓ 支持

API 访问指南

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

API 端点chat/completions

Model IDminimax/minimax-m3

定价