minimax/minimax-m3
Data di rilascio: 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.
Prezzi
Pay-per-use
Nessun costo iniziale, paga solo per ciò che usi
Prova il modello
Utilizzo API
Usa i seguenti esempi di codice per integrare la nostra 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;
}Introduzione al modello
MiniMax: MiniMax M3
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.
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
Info
Funzionalità supportate
Guida all'accesso API
Minimax M3 API
minimax/minimax-m3
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.
Input
$0.6 /M
Output
$2.4 /M
Contesto
1049K
Output max
512K
Vision
Supportato
Uso strumenti
Supportato
Prova Minimax M3 su WaveSpeedAI
Accedi a Minimax M3 tramite la nostra API unificata — compatibile con OpenAI, senza cold start, prezzi trasparenti.
Domande frequenti su Minimax M3
Quanto costa Minimax M3 via API?+
Prezzi su WaveSpeedAI: $0.60 per milione di token in input e $2.40 per milione di token in output. Prompt caching e batch processing sono fatturati separatamente e riducono il costo effettivo su carichi lunghi e ripetitivi.
Qual è la context window di Minimax M3?+
Minimax M3 supporta fino a 1049K token di contesto e fino a 512K token di output per richiesta.
Minimax M3 è compatibile con OpenAI?+
WaveSpeedAI espone Minimax M3 su https://llm.wavespeed.ai/v1 tramite l’interfaccia Chat Completions compatibile con OpenAI. Per la maggior parte dei client OpenAI SDK basta cambiare base URL e API key; i campi opzionali dipendono dal modello.
Come si inizia con Minimax M3?+
Accedi a WaveSpeedAI, crea una API key in Access Keys e invia una richiesta a https://llm.wavespeed.ai/v1/chat/completions con il model id mostrato sopra. Consulta il catalogo attuale per disponibilità, funzionalità e prezzi.