minimax/minimax-m2.7
204,800 context · $0.30/M input tokens · $1.20/M output tokens
MiniMax M2.7 is a next-generation flagship text model designed for agent-centric workflows, with strong improvements in coding, complex office tasks, and long-context reasoning. Built on the OpenClaw (Agent Harness) framework, it enables continuous self-improvement in real-world environments, allowing the model to actively participate in execution and decision-making for higher-quality and more efficient task completion.
定价
按量付费
无需预付费用，仅按实际使用量付费
试用模型
API 使用
使用以下代码示例接入我们的 API：
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-m2.7",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)模型介绍
Minimax minimax-m2.7
MiniMax-M2
MiniMax-M2.7 represents the journey of recursive self-improvement with enhanced reasoning and agentic capabilities.
Why It Looks Great
- MoE (Mixture of Experts) architecture for efficient processing
- 204800 context window for long document handling
- Competitive pricing at $0.3/$1.2 per million tokens
Key Features
- Context Window: 204800 tokens
- Max Output: N/A tokens
- Vision: Supported
- Function Calling: Supported
Specifications
| Specification | Value |
|---|---|
| Provider | Minimax |
| Model Type | Large Language Model (LLM) |
| Architecture | MoE (Mixture of Experts) |
| Context Window | 204800 tokens |
| Max Output | tokens |
| Input | Text |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
Pricing
| Token Type | Cost per Million Tokens |
|---|---|
| Input | $0.3 |
| Output | $1.2 |
How to Use
- Write your prompt — describe the task, provide context, and specify 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-m2.7
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-m2.7",
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-m2.7",
"messages": [{"role": "user", "content": "Hello!"}]
}'Notes
- Model: minimax/minimax-m2.7
- Provider: Minimax
信息
支持功能
API 访问指南
Minimax M2.7 API
minimax/minimax-m2.7
MiniMax M2.7 is a next-generation flagship text model designed for agent-centric workflows, with strong improvements in coding, complex office tasks, and long-context reasoning. Built on the OpenClaw (Agent Harness) framework, it enables continuous self-improvement in real-world environments, allowing the model to actively participate in execution and decision-making for higher-quality and more efficient task completion.
输入
$0.3 /M
输出
$1.2 /M
上下文
205K
工具调用
支持
关于 Minimax M2.7 的常见问题
Minimax M2.7 API 多少钱?+
WaveSpeedAI 定价:输入每百万 token $0.30,输出每百万 token $1.20。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 M2.7 的上下文窗口是多大?+
Minimax M2.7 单次请求最多支持 205K 上下文 token,输出最多 — token。
Minimax M2.7 是否兼容 OpenAI?+
是的。WaveSpeedAI 通过 https://llm.wavespeed.ai/v1 的 OpenAI 兼容端点提供 Minimax M2.7。把官方 OpenAI SDK 的 base URL 指向该地址,使用 WaveSpeedAI 的 API Key 即可,无需任何其他代码改动。
如何开始使用 Minimax M2.7?+
登录 WaveSpeedAI,在 Access Keys 中生成 API Key,使用上方显示的 model id 向 https://llm.wavespeed.ai/v1/chat/completions 发送请求。新账户可获得免费额度,用于试用 Minimax M2.7。