MiniMax M1 overview
MiniMax M1 by MiniMax
MiniMax M1 API is a frontier Mixture-of-Experts model with a 1M-token context window and 80K output limit.
MiniMax M1 specs
- Model ID
minimax/m1- Developer
- MiniMax
- Context window
- 1,000,000 tokens
- Max output
- 40,960 tokens
- Input
- Text, Image
- Output
- Text
- API
- OpenAI-compatible, base URL
https://api.aimlapi.com/v1
MiniMax M1 Description
MiniMax M1 is an open-weight Mixture-of-Experts transformer with 456B total parameters and up to 1 million tokens of context. With 80K output capacity, it is purpose-built for massive input processing, logical analysis, and deep code reasoning. Ideal for RAG pipelines, legal and scientific workflows, and agentic tools.
Technical Parameters
- Context Window: 1,000,000 tokens
- Output Capacity: Up to 80,000 tokens
- Architecture: Sparse MoE Transformer with Lightning Attention
- Parameters: 456B (45B active per token)
Key Capabilities
- Full-scale document and codebase comprehension across million-token inputs
- Fast inference and optimized MoE routing
- Efficient serving and compatibility
- Supports tool use and planning in agentic workflows
Optimal Use Cases
- Code Engineering: Process and refactor large repositories in a single pass
- Document Analytics: Perform reasoning over legal, technical, or regulatory data
- RAG Systems: Use as a long-context backend for question answering
- Mathematical Reasoning: Step-by-step symbolic and logical analysis
Comparison with Other Models
- Vs. GPT-4o: M1 offers 1M context tokens vs GPT-4o’s 128K; better for large inputs
- Vs. Claude 4 Opus: M1 provides more context (1M vs 128K); both excel in reasoning
- Vs. Gemini 2.5 Pro: M1 leads in token capacity and scale for structured inputs
Limitations
- No vision or multimodal input support
- Some tools/platforms may require manual integration
Use cases
- Codebase Refactoring: Process and refactor full-scale repositories with reasoning across multiple files.
- Legal Document Analysis: Analyze 100K+ token legal documents in one context window.
- Agentic Task Execution: Execute multi-step tools and actions over long reasoning chains.
- Scientific Literature Synthesis: Summarize, compare, and extract insight from multiple large research papers.
- Structured QA over Logs: Perform question answering over full-session logs without truncation.
Capabilities
- Function calling
- Streaming
- Structured outputs
- Reasoning
MiniMax M1 API pricing
| Usage | Price | Unit |
|---|---|---|
| Input | $0.4 | 1M tokens |
| Output | $2.2 | 1M tokens |
Prices from the AI/ML API price list, checked on Nov 4, 2026.
MiniMax M1 vs other models: token prices
AI/ML API input and output rates for 5 models, per million tokens.
| Model | Input | Output |
|---|---|---|
 MiniMax M1 | $0.4 | $2.2 |
| MiniMax M3.1 Flash | $0.15 | $0.6 |
| MiniMax M3 | $0.3 | $1.2 |
| MiniMax M2.1 Highspeed | $0.6 | $2.4 |
| MiniMax M2.7 Highspeed | $0.6 | $2.4 |
How to use the MiniMax M1 API
View docs
Build with your agent
Give your agent the model details, code and documentation.
1Get your API key
Create API keyexport AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"2Make your first request
curl 'https://api.aimlapi.com/v1/chat/completions' \
-H "Authorization: Bearer $AIMLAPI_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "minimax/m1",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}'import os
import requests
headers = {
"Authorization": f"Bearer {os.environ['AIMLAPI_KEY']}",
"Content-Type": "application/json",
}
payload = {
"model": "minimax/m1",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}
response = requests.post("https://api.aimlapi.com/v1/chat/completions", headers=headers, json=payload, timeout=120)
response.raise_for_status()
print(response.json())const response = await fetch("https://api.aimlapi.com/v1/chat/completions", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"model": "minimax/m1",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}),
});
if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());Models similar to MiniMax M1
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MiniMax M1 FAQ
What is the context window of MiniMax M1?
MiniMax M1 has a 1,000,000 tokens context window and can return up to 40,960 tokens.
What inputs and outputs does MiniMax M1 support?
MiniMax M1 takes text as input and returns text.
What is the model ID for MiniMax M1?
Use minimax/m1 as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.
How much does MiniMax M1 cost?
MiniMax M1 costs $0.4 input and $2.2 output per 1M tokens on AI/ML API, billed as you go with no subscription.
Does MiniMax M1 support streaming?
Yes, MiniMax M1 can stream responses as they are generated.
Who created MiniMax M1?
MiniMax M1 was built by MiniMax.