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MiniMax M1
minimaxai/minimax-m1-80k
MiniMax-M1: The World's First Open-Weight, Large-Scale Hybrid Attention Inference Model
MiniMax-M1 adopts a Mixture of Experts (MoE) architecture and integrates the Flash Attention mechanism. The model contains a total of 456 billion parameters, with 45.9 billion parameters activated per token.
Natively, the M1 model supports a context length of 1 million tokens—8 times that of DeepSeek R1. Additionally, by combining the CISPO algorithm with an efficient hybrid attention design for reinforcement learning training, MiniMax-M1 achieves industry-leading performance in long-context reasoning and real-world software engineering scenarios.
Features
Serverless API
Docs
minimaxai/minimax-m1-80k is available via Novita's serverless API, where you pay per token. There are several ways to call the API, including OpenAI-compatible endpoints with exceptional reasoning performance.
On-demand Deployments
Docs
On-demand deployments allow you to use minimaxai/minimax-m1-80k on dedicated GPUs with high-performance serving stack with high reliability and no rate limits.
Available Serverless
Run queries immediately, pay only for usage
Input$0.55 / M Tokens
Output$2.2 / M Tokens
Use the following code examples to integrate with our API:
1from openai import OpenAI
2
3client = OpenAI(
4 api_key="<Your API Key>",
5 base_url="https://api.novita.ai/openai"
6)
7
8response = client.chat.completions.create(
9 model="minimaxai/minimax-m1-80k",
10 messages=[
11 {"role": "system", "content": "You are a helpful assistant."},
12 {"role": "user", "content": "Hello, how are you?"}
13 ],
14 max_tokens=40000,
15 temperature=0.7
16)
17
18print(response.choices[0].message.content)Info
Provider
MiniMax
Quantization
bf16
Supported Functionality
Context Length
1000000
Max Output
40000
Function Calling
Supported
Reasoning
Supported
Input Capabilities
text
Output Capabilities
text