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.
Preços
Pagamento por uso
Sem custo inicial, pague apenas pelo que usar
Experimentar o modelo
Uso da API
Use os exemplos de código abaixo para integrar com nossa 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)Introdução do modelo
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
Info
Funcionalidades suportadas
Guia de acesso à API
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.
Entrada
$0.3 /M
Saída
$1.2 /M
Contexto
205K
Uso de ferramentas
Suportado
Experimente Minimax M2.7 no WaveSpeedAI
Acesse Minimax M2.7 através da nossa API unificada — compatível com OpenAI, sem inicializações a frio, preços transparentes.
Perguntas frequentes sobre Minimax M2.7
Quanto custa Minimax M2.7 via API?+
Preços no WaveSpeedAI: $0.30 por milhão de tokens de entrada e $1.20 por milhão de tokens de saída. Prompt caching e batch processing são cobrados separadamente e reduzem o custo efetivo em cargas longas e repetitivas.
Qual é a janela de contexto do Minimax M2.7?+
Minimax M2.7 suporta até 205K tokens de contexto e até — tokens de saída por requisição.
Minimax M2.7 é compatível com OpenAI?+
Sim. O WaveSpeedAI expõe o Minimax M2.7 através de um endpoint compatível com OpenAI em https://llm.wavespeed.ai/v1. Aponte o SDK oficial da OpenAI para esta base URL com sua chave API do WaveSpeedAI — sem outras alterações no código.
Como começo a usar o Minimax M2.7?+
Entre no WaveSpeedAI, crie uma chave API em Access Keys, então envie uma requisição para https://llm.wavespeed.ai/v1/chat/completions com o model id mostrado acima. Contas novas recebem créditos grátis para avaliar o Minimax M2.7.