MiniMax M1 API:
Think Bigger, Reason Further
New benchmark in ultra-long context, advanced reasoning, and scalable AI workflows
MiniMax M1: Deep Thinking
at Million-Token Scale
MiniMax M1, the latest open-weight model from MiniMax, processes up to 1 million token inputs with its 456B-parameter Mixture-of-Experts transformer architecture. M1 achieves top-tier results in coding, logic, and software engineering benchmarks, setting new standards for efficiency and performance. Its lightning-fast attention mechanism ensures quick and accurate outputs, ideal for professional-grade applications.
Extended Context Performance
MiniMax M1 handles inputs up to 1 million tokens, enabling seamless processing of extensive codebases, comprehensive documents, and detailed logical reasoning without segmentation. Its ultra-long context capability ensures deep comprehension and continuity across massive inputs.
Scalable Efficiency
M1 uses an efficient Mixture-of-Experts design, activating around 45.9B parameters per token, drastically reducing computational cost. Its specialized attention mechanisms allow rapid inference even at unprecedented context lengths, ideal for cost-effective, high-throughput deployments.
Superior Reasoning Capabilities
Proven by top rankings in critical benchmarks like SWE-bench, LiveCodeBench, and AIME 2025, MiniMax M1 consistently outperforms other models in complex reasoning tasks. It provides reliable, high-quality outputs crucial for enterprise-level decision-making.
Scale Enterprise Tasks With MiniMax M1
Maximize Your Workflow Efficiency
Software Development
MiniMax M1 streamlines complex multi-file refactors and in-depth codebase analysis, significantly reducing the time required for large software projects. Its extensive context and precise reasoning ensure consistent, high-quality code improvements.
Knowledge Management
Enhance data-driven decisions by processing massive documents and knowledge bases in one pass. MiniMax M1 efficiently summarizes and extracts insights from legal, financial, and research data, supporting better strategic outcomes.
AI Agents and Automation
Power sophisticated agentic systems capable of handling multiple tools, memory states, and step-by-step logical operations. MiniMax M1 excels in automating complex workflows, from data extraction to actionable intelligence.
Technical Comparison
MiniMax M1 establishes a new standard for long-context reasoning, surpassing other leading AI models in scalability and performance.
MiniMax M1 vs GPT-4o
GPT-4o supports up to 128K tokens with strong multimodal capabilities, but MiniMax M1's million-token context window and open-source flexibility offer deeper reasoning and greater customization options for enterprise use.
Learn more about GPT-4o API.
MiniMax M1 vs Claude 4 Opus
Claude 4 Opus delivers robust coding capabilities within its 128K token limit. However, MiniMax M1’s significantly larger context enables extended multi-file projects and deeper sustained reasoning tasks at scale.
Learn more about Claude 4 Opus.
MiniMax M1 vs Gemini 2.5 Pro
Gemini 2.5 Pro provides excellent multimodal reasoning within its large context window. Yet, MiniMax M1 surpasses Gemini 2.5 Pro in maximum context length and sustained high-performance reasoning, particularly suited for extremely complex and long-form tasks.
Learn more about Gemini 2.5 Pro API.
Why Choose AI/ML API solution?
AI/ML API provides scalability, faster deployment, and access to 200+ advanced machine learning models without the need for extensive in-house expertise or infrastructure.
Easy To Use
Our API allows seamless integration of powerful AI capabilities into your applications, regardless of your coding experience. Simply swap your API key to begin using the AI/ML API.
Scalable
AI/ML API provides flexibility for business growth since you can scale resources by purchasing more tokens as needed, ensuring optimal performance and cost efficiency
Affordable
We offer flat, predictable pricing, payable by card or cryptocurrency, keeping it the lowest on the market and affordable for everyone.
import requests
import json # for getting a structured output with indentation
response = requests.post(
"https://api.aimlapi.com/v1/chat/completions",
headers={
"Content-Type":"application/json",
# Insert your AIML API Key instead of <YOUR_AIMLAPI_KEY>:
"Authorization":"Bearer <YOUR_AIMLAPI_KEY>",
"Content-Type":"application/json"
},
json={
"model":"minimax/m1",
"messages":[
{
"role":"user",
# Insert your question for the model here, instead of Hello:
"content":"Hello"
}
]
}
)
data = response.json()
print(json.dumps(data, indent=2, ensure_ascii=False))Getting started with
M1 by MiniMax
Visit AI Playground to quickly try MiniMax M1.
For more information about technical features, please refer to MiniMax M1 documentation page.