MiniMax-01: Advanced Language Model with 456B Parameters
Experience a powerful language model featuring hybrid attention and MoE architecture, excelling in reasoning, mathematics, and coding tasks with up to 4M token context length
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Key Features
Discover the powerful capabilities of MiniMax-01
Hybrid Architecture
Innovative combination of Lightning Attention, Softmax Attention, and Mixture-of-Experts (MoE) with 456B total parameters and 45.9B activated per token
- •80-layer architecture
- •64 attention heads
- •32 expert networks
- •Top-2 routing strategy
Benchmark Performance
Outstanding results across multiple benchmarks including MMLU (88.5%), MMLU-Pro (75.7%), and GSM8K (94.8%)
- •Strong mathematical reasoning
- •Advanced coding capabilities
- •Complex problem solving
- •Long context understanding
Long Context Processing
Support for up to 4 million tokens during inference and 1 million tokens during training
- •Extended context window
- •Efficient token processing
- •Document comprehension
- •Large-scale analysis
Advanced Attention
Hybrid attention mechanism with softmax attention after every 7 lightning attention layers
- •Enhanced context understanding
- •Efficient information processing
- •Balanced attention distribution
- •Optimized performance
Expert Networks
32 specialized expert networks with 9216 hidden dimension and efficient routing strategy
- •Specialized processing
- •Dynamic routing
- •Task optimization
- •Efficient computation
Model Architecture
State-of-the-art architecture designed for optimal performance and efficiency
- •Hidden size: 6144
- •Vocab size: 200,064
- •RoPE positional encoding
- •Advanced parameter sharing
Versatile Applications
Comprehensive capabilities across various domains including mathematics, coding, and reasoning
- •Mathematical computation
- •Code generation
- •Complex reasoning
- •Knowledge retrieval
Performance Optimization
Highly optimized for both training and inference with advanced techniques
- •Efficient parameter activation
- •Balanced load distribution
- •Optimized memory usage
- •Fast inference speed
MiniMax-01 Achievements
Leading performance in language and vision tasks
Benchmark Excellence
MiniMax-01 achieves outstanding performance across benchmarks, including 88.5% on MMLU, 75.7% on MMLU-Pro, and 94.8% on GSM8K, demonstrating strong capabilities in reasoning and problem-solving.
Advanced Architecture
Featuring 456B parameters with 45.9B activated per token, MiniMax-01 combines Lightning Attention, Softmax Attention, and MoE for optimal performance.
Long Context Processing
Supporting up to 4M tokens during inference and 1M tokens during training, enabling effective processing of extensive documents and complex tasks.
Vision Capabilities
MiniMax-VL-01 extends the model with advanced visual processing, featuring dynamic resolution from 336×336 to 2016×2016 and achieving strong performance on visual tasks.
MiniMax-01 Performance Metrics
General Knowledge & Reasoning
Programming & Development
Mathematical Reasoning
Technical Specifications
Explore the advanced architecture and capabilities of MiniMax-01
MiniMax-01 Architecture Details
Advanced neural architecture combining Lightning Attention and MoE
MiniMax-01 Research
Advancing AI through innovative architectures and techniques
Hybrid Architecture
Revolutionary combination of Lightning Attention, Softmax Attention, and Mixture-of-Experts (MoE) architecture with advanced parallel strategies
Long Context Processing
Extended context capabilities supporting up to 4M tokens during inference through innovative techniques like LASP+ and varlen ring attention
Efficient Scaling
Advanced parallel strategies including Linear Attention Sequence Parallelism Plus (LASP+) and Expert Tensor Parallel (ETP)
Technical Paper
Read our research paper 'MiniMax-01: Scaling Foundation Models with Lightning Attention' detailing our innovative architecture and achievements.
Read the PaperAbout MiniMax
Advancing AI through innovative architectures
Company Overview
MiniMax is dedicated to developing state-of-the-art AI models through innovative architectures and advanced research in attention mechanisms and expert systems.
Core Technology
Our flagship models combine Lightning Attention, Softmax Attention, and Mixture-of-Experts (MoE) architectures to achieve superior performance across various tasks.
Download MiniMax-01 Models
Choose between MiniMax-Text-01 and MiniMax-VL-01 models
MiniMax-Text-01
Advanced language model with hybrid attention and MoE architecture
- •456B total parameters
- •45.9B activated parameters
- •4M token context length
- •80-layer architecture
MiniMax-VL-01
Vision-language model built on MiniMax-Text-01
- •303M ViT parameters
- •Dynamic resolution
- •336×336 to 2016×2016
- •Advanced visual processing
Installation Instructions
Access models through Hugging Face:
# For Text Model
git lfs install
git clone https://huggingface.co/MiniMaxAI/MiniMax-Text-01
# For VL Model
git lfs install
git clone https://huggingface.co/MiniMaxAI/MiniMax-VL-01MiniMax-01 Deployment Options
Quantization Options
Support for int8 quantization with specialized modules for optimal performance
- Int8 weights quantization
- Selective module conversion
- Optimized memory usage
Multi-GPU Deployment
Efficient distribution across multiple GPUs with advanced parallel strategies
- Device map configuration
- Layer distribution
- Balanced workload
Model Loading
Flexible loading options with bfloat16 support and buffer management
- Bfloat16 precision
- Buffer offloading
- Custom device mapping
Generation Settings
Configurable generation parameters for optimal output control
- Custom token limits
- Cache management
- Response formatting
How to Use MiniMax-01
Multiple ways to access and utilize MiniMax-01's capabilities
Choose Access Method
Select between our online chat interface (Hailuo AI), API platform, or direct model access through Hugging Face
Online Chat
Visit www.hailuo.ai to start chatting with MiniMax-01 immediately - no registration required
API Integration
Access our API platform at intl.minimaxi.com for developer documentation and integration guides
Model Deployment
Download and deploy models from Hugging Face with support for both text and vision-language tasks
FAQ
Common questions about MiniMax-01
What is MiniMax-01's architecture?
MiniMax-01 features a hybrid architecture combining Lightning Attention, Softmax Attention, and Mixture-of-Experts (MoE). It has 456B total parameters with 45.9B activated per token, 80 layers, and 64 attention heads.
What is the context length of MiniMax-01?
MiniMax-01 supports up to 4 million tokens during inference and 1 million tokens during training, enabling effective processing of long documents and complex tasks.
How does MiniMax-01 perform on benchmarks?
MiniMax-01 achieves strong results across various benchmarks, including 88.5% on MMLU, 75.7% on MMLU-Pro, and 94.8% on GSM8K, demonstrating excellent capabilities in reasoning and problem-solving.
What is MiniMax-VL-01?
MiniMax-VL-01 is our vision-language model built on MiniMax-Text-01. It features a 303M parameter Vision Transformer (ViT) and supports dynamic resolution from 336×336 to 2016×2016.
How can I access MiniMax-01?
You can access MiniMax-01 through our online chat interface (Hailuo AI), API platform (intl.minimaxi.com), or download the models from Hugging Face.
What deployment options are available?
MiniMax-01 supports various deployment options including int8 quantization, multi-GPU distribution, and flexible loading with bfloat16 support.
What are the hardware requirements?
The model can be deployed across multiple GPUs with customizable device mapping and load balancing for optimal performance.
Is there an API available?
Yes, we provide a comprehensive API platform at intl.minimaxi.com with developer documentation and integration guides.
Get Started with MiniMax-01
Access MiniMax API
Integrate MiniMax-01's capabilities into your applications through our developer platform
Visit PlatformExplore Models
Access MiniMax-01 models through Hugging Face, available in both text and vision-language versions
View Models