DeepSeek V3: Advanced AI
Language Model with 671B
Parameters
Discover revolutionary AI language models—smarter, faster, and more efficient at coding, reasoning, and crunching numbers.
- 671B Parameters
- Advanced Coding
- Efficient Training
Free Website Integration
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Download DeepSeek Mobile App
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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
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Multi-head Latent Attention (MLA)
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Auxiliary-loss-free load balancing
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DeepSeekMoE architecture
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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
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Top scores in coding competitions
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Advanced mathematical computation
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Multilingual capabilities
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Complex reasoning tasks
Efficient Training
Groundbreaking training approach requiring only 2.788M H800 GPU hours, with remarkable cost efficiency of $5.5M
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FP8 mixed precision training
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Optimized training framework
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Stable training process
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No rollbacks required
Versatile Deployment
Multiple deployment options supporting NVIDIA, AMD GPUs and Huawei Ascend NPUs for flexible integration
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Cloud deployment ready
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Local inference support
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Multiple hardware platforms
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Optimized serving options
Advanced Coding Capabilities
Superior performance in programming tasks, excelling in both competitive coding and real-world development scenarios
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Multi-language support
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Code completion
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Bug detection
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Code optimization
Enterprise-Ready Security
Comprehensive security measures and compliance features for enterprise deployment and integration
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Access control
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Data encryption
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Audit logging
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Compliance ready
Extensive Training Data
Pre-trained on 14.8T diverse and high-quality tokens, ensuring broad knowledge and capabilities
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Diverse data sources
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Quality-filtered content
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Multiple domains
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Regular updates
Innovation Leadership
Pioneering advancements in AI technology through open collaboration and continuous innovation
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Research leadership
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Open collaboration
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Community driven
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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.
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
Breaking new ground in open-source AI development
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 Training Process
Comprehensive training pipeline optimized for performance and stability
DeepSeek V3 Core Capabilities
Comprehensive set of abilities spanning multiple domains
Performance Optimization
Cutting-edge techniques for maximum 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.
About 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)
Size: 685GB
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Pre-trained on 14.8T tokens
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128K context length
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FP8 weights
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671B total parameters
DeepSeek V3 Chat Model
Fine-tuned model optimized for dialogue and interaction
Size: 685GB
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Enhanced reasoning
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128K context length
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Improved instruction following
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671B total parameters
Download DeepSeek V3 Models
Choose between the base and chat-tuned versions of DeepSeek V3
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
FAQ
Learn more about DeepSeek-R1
Are there smaller versions of DeepSeek-R1 available?
Yes, through successful model distillation, we offer smaller models that preserve DeepSeek-R1's core reasoning capabilities while being more resource-efficient.
How does DeepSeek-R1 perform in mathematical tasks?
DeepSeek-R1 achieves exceptional performance in mathematics, with 79.8% accuracy on AIME 2024 and 97.3% on MATH-500, demonstrating advanced reasoning capabilities.
What are DeepSeek-R1's programming capabilities?
DeepSeek-R1 demonstrates expert-level programming skills with a 2029 Elo rating on Codeforces, surpassing 96.3% of human participants.
What makes DeepSeek-R1 unique?
DeepSeek-R1 is unique in its pure reinforcement learning approach, which naturally developed sophisticated reasoning behaviors including self-verification and extended chain of thought capabilities.
How was DeepSeek-R1 trained?
DeepSeek-R1 uses a multi-stage training approach, starting with pure reinforcement learning (DeepSeek-R1-Zero), followed by comprehensive fine-tuning and optimization stages.
What types of problems can DeepSeek-R1 solve?
DeepSeek-R1 excels in complex reasoning tasks, including mathematical proofs, competitive programming, and knowledge-based problems, achieving high scores across various benchmarks.
How does DeepSeek-R1 compare to other models?
DeepSeek-R1 achieves performance comparable to leading models, with superior results in mathematical reasoning (AIME, MATH-500) and programming tasks (Codeforces).
What are the future development plans for DeepSeek-R1?
We're focusing on enhancing capabilities in function calling, multi-turn dialogue, and complex role-playing, while improving reinforcement learning efficiency in various tasks.
Get Started with DeepSeek-R1
Try DeepSeek-R1 API
Access DeepSeek-R1's advanced reasoning capabilities through our developer-friendly API
Explore Research
Learn about our revolutionary reinforcement learning approach and technical innovations
Try DeepSeek-R1 Chat
Experience our advanced reasoning capabilities through interactive chat
