minimax/minimax-m2
196,608 context · $0.30/M input tokens · $1.20/M output tokens
MiniMax-M2 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows. With 10 billion activated parameters (230 billion total), it delivers near-frontier intelligence across general reasoning,...
定價
按用量付費
無需預付費用，僅按實際使用量付費
試用模型
API 使用
使用以下程式碼範例整合我們的 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",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)模型介紹
Minimax minimax-m2
MiniMax-M2 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows
MiniMax-M2 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows.
Why It Looks Great
- MoE (Mixture of Experts) architecture for efficient processing
- 196608 context window for long document handling
- Competitive pricing at $0.3/$1.1 per million tokens
Key Features
- Context Window: 196608 tokens
- Max Output: 65536 tokens
- Vision: Supported
- Function Calling: Supported
Specifications
| Specification | Value |
|---|---|
| Provider | Minimax |
| Model Type | Large Language Model (LLM) |
| Architecture | MoE (Mixture of Experts) |
| Context Window | 196608 tokens |
| Max Output | 65536 tokens |
| Input | Text |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
Pricing
| Token Type | Cost per Million Tokens |
|---|---|
| Input | $0.3 |
| Output | $1.1 |
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
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",
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",
"messages": [{"role": "user", "content": "Hello!"}]
}'Notes
- Model: minimax/minimax-m2
- Provider: Minimax
資訊
支援功能
API 存取指南
Minimax M2 API
minimax/minimax-m2
MiniMax-M2 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows. With 10 billion activated parameters (230 billion total), it delivers near-frontier intelligence across general reasoning,...
輸入
$0.3 /M
輸出
$1.2 /M
上下文
197K
最大輸出
197K
工具調用
支援
關於 Minimax M2 的常見問題
Minimax M2 API 多少錢?+
WaveSpeedAI 定價:輸入每百萬 token $0.30,輸出每百萬 token $1.20。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 M2 的上下文視窗有多大?+
Minimax M2 每次請求最多支援 197K 上下文 token,輸出最多 197K token。
Minimax M2 是否相容 OpenAI?+
是的。WaveSpeedAI 透過 https://llm.wavespeed.ai/v1 的 OpenAI 相容端點提供 Minimax M2。將官方 OpenAI SDK 的 base URL 指向該位址,使用 WaveSpeedAI 的 API Key 即可,無需其他程式碼變更。
如何開始使用 Minimax M2?+
登入 WaveSpeedAI,在 Access Keys 建立 API Key,使用上方顯示的 model id 向 https://llm.wavespeed.ai/v1/chat/completions 發送請求。新帳號將獲得免費額度,用於試用 Minimax M2。