DeepSeek V3: Advanced AI Language Model with 671B Parameters
Experience the next generation of language models with groundbreaking efficiency in reasoning, coding, and mathematical computation
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Key Features
Discover the powerful capabilities that make DeepSeek V3 stand out
Advanced MoE Architecture
Revolutionary 671B parameter model with only 37B activated per token, achieving optimal efficiency through innovative load balancing
- •Multi-head Latent Attention (MLA)
- •Auxiliary-loss-free load balancing
- •DeepSeekMoE architecture
- •Multi-token prediction objective
State-of-the-Art Performance
Exceptional results across multiple benchmarks including MMLU (87.1%), BBH (87.5%), and mathematical reasoning tasks
- •Top scores in coding competitions
- •Advanced mathematical computation
- •Multilingual capabilities
- •Complex reasoning tasks
Efficient Training
Groundbreaking training approach requiring only 2.788M H800 GPU hours, with remarkable cost efficiency of $5.5M
- •FP8 mixed precision training
- •Optimized training framework
- •Stable training process
- •No rollbacks required
Versatile Deployment
Multiple deployment options supporting NVIDIA, AMD GPUs and Huawei Ascend NPUs for flexible integration
- •Cloud deployment ready
- •Local inference support
- •Multiple hardware platforms
- •Optimized serving options
Advanced Coding Capabilities
Superior performance in programming tasks, excelling in both competitive coding and real-world development scenarios
- •Multi-language support
- •Code completion
- •Bug detection
- •Code optimization
Enterprise-Ready Security
Comprehensive security measures and compliance features for enterprise deployment and integration
- •Access control
- •Data encryption
- •Audit logging
- •Compliance ready
Extensive Training Data
Pre-trained on 14.8T diverse and high-quality tokens, ensuring broad knowledge and capabilities
- •Diverse data sources
- •Quality-filtered content
- •Multiple domains
- •Regular updates
Innovation Leadership
Pioneering advancements in AI technology through open collaboration and continuous innovation
- •Research leadership
- •Open collaboration
- •Community driven
- •Regular improvements
DeepSeek V3 in the Media
Breaking new ground in open-source AI development
Breakthrough Performance
DeepSeek V3 outperforms both open and closed AI models in coding competitions, particularly excelling in Codeforces contests and Aider Polyglot tests.
Massive Scale
Built with 671 billion parameters and trained on 14.8 trillion tokens, making it 1.6 times larger than Meta's Llama 3.1 405B.
Cost-Effective Development
Trained in just two months using Nvidia H800 GPUs, with a remarkably efficient development cost of $5.5 million.
DeepSeek V3 in Action
Watch how DeepSeek V3 revolutionizes open-source AI capabilities
DeepSeek V3: Revolutionary Open Source AI
An in-depth look at DeepSeek V3's capabilities and performance compared to other leading AI models.
DeepSeek V3 Performance Metrics
DeepSeek V3 Language Understanding
DeepSeek V3 Coding
DeepSeek V3 Mathematics
Technical Specifications
Explore the advanced technical capabilities and architecture that power DeepSeek V3
DeepSeek V3 Architecture Details
Advanced neural architecture designed for optimal performance and efficiency
DeepSeek V3 Research
Advancing the boundaries of language model capabilities
Novel Architecture
Innovative Mixture-of-Experts (MoE) architecture with auxiliary-loss-free load balancing strategy
Training Methodology
Advanced FP8 mixed precision training framework validated on large-scale model training
Technical Paper
Read our comprehensive technical paper detailing the architecture, training process, and evaluation results of DeepSeek V3.
Read the PaperAbout DeepSeek
Pioneering the future of open-source AI development
Company Background
Backed by High-Flyer Capital Management, DeepSeek aims to achieve breakthrough advances in AI technology through open collaboration and innovation.
Infrastructure
Utilizing advanced computing clusters including 10,000 Nvidia A100 GPUs, DeepSeek demonstrates exceptional capabilities in large-scale model training.
Download DeepSeek V3 Models
Choose between the base and chat-tuned versions of DeepSeek V3
DeepSeek V3 Base Model
The foundation model with 671B parameters (37B activated)
- •Pre-trained on 14.8T tokens
- •128K context length
- •FP8 weights
- •671B total parameters
DeepSeek V3 Chat Model
Fine-tuned model optimized for dialogue and interaction
- •Enhanced reasoning
- •128K context length
- •Improved instruction following
- •671B total parameters
Installation Instructions
Download using Git LFS (recommended method):
# For Base Model
git lfs install
git clone https://huggingface.co/deepseek-ai/DeepSeek-V3-Base
# For Chat Model
git lfs install
git clone https://huggingface.co/deepseek-ai/DeepSeek-V3DeepSeek V3 Deployment Options
DeepSeek V3 Local Deployment
Run locally with DeepSeek-Infer Demo supporting FP8 and BF16 inference
- Simple setup
- Lightweight demo
- Multiple precision options
DeepSeek V3 Cloud Integration
Deploy on cloud platforms with SGLang and LMDeploy support
- Cloud-native deployment
- Scalable infrastructure
- Enterprise-ready
DeepSeek V3 Hardware Support
Compatible with NVIDIA, AMD GPUs and Huawei Ascend NPUs
- Multi-vendor support
- Optimized performance
- Flexible deployment
How to Use DeepSeek V3
Start chatting with DeepSeek V3 in three simple steps
Visit Chat Page
Click the "Try Chat" button at the top of the page to enter the chat interface
Enter Your Question
Type your question in the chat input box
Wait for Response
DeepSeek V3 will quickly generate a response, usually within seconds
FAQ
Learn more about DeepSeek V3
What makes DeepSeek V3 unique?
DeepSeek V3 features a 671B parameter MoE architecture, incorporating innovations like multi-token prediction and auxiliary-free load balancing, delivering exceptional performance across various tasks.
How can I access DeepSeek V3?
You can access DeepSeek V3 through our online demo platform and API service, or download the model weights for local deployment.
In which tasks does DeepSeek V3 excel?
DeepSeek V3 excels in mathematics, programming, reasoning, and multilingual tasks, consistently achieving top scores in benchmark evaluations.
What are the hardware requirements for running DeepSeek V3?
DeepSeek V3 supports various deployment options, including NVIDIA GPUs, AMD GPUs, and Huawei Ascend NPUs, with multiple framework choices for optimal performance.
Is DeepSeek V3 available for commercial use?
Yes, DeepSeek V3 is available for commercial use. Please refer to the model license agreement for specific terms of use.
How does DeepSeek V3 compare to other language models?
DeepSeek V3 outperforms other open-source models in various benchmarks and achieves performance comparable to leading closed-source models.
Which deployment frameworks does DeepSeek V3 support?
DeepSeek V3 can be deployed using various frameworks including SGLang, LMDeploy, TensorRT-LLM, vLLM, and supports FP8 and BF16 inference modes.
What is the context window size of DeepSeek V3?
DeepSeek V3 has a 128K context window, enabling effective processing and understanding of complex tasks and long-form content.
Get Started with DeepSeek V3
Try DeepSeek V3 API
Access DeepSeek V3's capabilities through our developer-friendly API platform
Start BuildingExplore on GitHub
Access the source code, documentation, and contribute to DeepSeek V3
View RepositoryTry DeepSeek V3 Chat
Experience DeepSeek V3's capabilities directly through our interactive chat interface
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