minimax/minimax-m3
Veröffentlichungsdatum: 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.
Preise
Pay-per-Use
Keine Vorabkosten, zahlen Sie nur, was Sie nutzen
Modell ausprobieren
API-Nutzung
Verwenden Sie die folgenden Codebeispiele zur Integration mit unserer 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;
}Modelleinführung
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
Unterstützte Funktionen
API-Zugriffsanleitung
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.
Eingabe
$0.6 /M
Ausgabe
$2.4 /M
Kontext
1049K
Max. Ausgabe
512K
Vision
Unterstützt
Tool-Nutzung
Unterstützt
Minimax M3 auf WaveSpeedAI testen
Zugriff auf Minimax M3 über unsere einheitliche API — OpenAI-kompatibel, keine Kaltstarts, transparente Preise.
Häufige Fragen zu Minimax M3
Wie viel kostet die Minimax M3-API?+
Preise auf WaveSpeedAI: $0.60 pro Million Input-Tokens und $2.40 pro Million Output-Tokens. Prompt-Caching und Batch-Verarbeitung werden separat berechnet und reduzieren die effektiven Kosten bei langen, sich wiederholenden Workloads.
Wie groß ist das Kontextfenster von Minimax M3?+
Minimax M3 unterstützt bis zu 1049K Kontext-Tokens und bis zu 512K Output-Tokens pro Anfrage.
Ist Minimax M3 OpenAI-kompatibel?+
WaveSpeedAI stellt Minimax M3 unter https://llm.wavespeed.ai/v1 über die OpenAI-kompatible Chat-Completions-Schnittstelle bereit. Bei den meisten OpenAI-SDK-Clients reichen Base-URL und API-Schlüssel; optionale Felder hängen vom Modell ab.
Wie starte ich mit Minimax M3?+
Melden Sie sich bei WaveSpeedAI an, erstellen Sie unter Access Keys einen API-Schlüssel und senden Sie eine Anfrage mit der oben gezeigten Modell-ID an https://llm.wavespeed.ai/v1/chat/completions. Verfügbarkeit, Fähigkeiten und Preise finden Sie im aktuellen Modellkatalog.