DeepSeek V4
Next-Generation AI Coding Assistant
Breakthrough Engram memory architecture, 1M+ token context window, and repository-level code analysis capabilities. The flagship model from Hangzhou DeepSeek Artificial Intelligence delivers an unprecedented programming experience for developers and enterprises worldwide.
Experience DeepSeek V4 NowWhy Choose DeepSeek V4
Leading technical architecture, exceptional performance, built for enterprise applications
1M+ Token Context
Process entire codebases while maintaining exceptional context retention. DeepSeek V4 performs repository-level analysis, tracking cross-file dependencies and API relationships with unprecedented accuracy.
Engram Memory Architecture
Revolutionary knowledge separation technology using N-gram embeddings with O(1) lookup. Stores static knowledge in CPU memory, freeing GPU resources for advanced reasoning tasks.
Repository-Level Code Analysis
Diagnose and repair complex bugs across multiple files simultaneously. DeepSeek V4 understands intricate import/export relationships and maintains architectural consistency throughout your projects.
Open Source & Local Deployment
Deploy open-weight models on your infrastructure. Supports quantization, batch processing, and private cloud deployment for regulated industries including finance and healthcare.
Superior Performance Benchmarks
Leading results on HumanEval, MMLU, and BBH benchmarks. DeepSeek V4 achieves exceptional coding accuracy while maintaining cost-effective operations.
Cost-Efficient API Pricing
DeepSeek Sparse Attention (DSA) technology reduces API costs by approximately 50% through intelligent token selection while improving long-context performance.
Advanced Architecture Powering DeepSeek V4
Breakthrough technical innovations redefining the boundaries of AI coding assistants
Engram Conditional Memory Core Innovation
Separates knowledge storage from reasoning computation using N-gram embeddings with constant-time O(1) hash-based lookup. Achieves +3.4 points on MMLU and +5.0 points on BBH compared to equivalent MoE models, while storing static knowledge in CPU RAM rather than expensive GPU VRAM.
mHC Technology Stability
Manifold-Constrained Hyper-Connections solve training instability when scaling models wider. Using the Sinkhorn-Knopp algorithm to constrain residual mixing matrices, mHC maintains signal stability across hundreds of layers with only 6.7% training overhead.
DeepSeek Sparse Attention Efficiency
Intelligent token selection using flash indexer technology focuses computational resources on important tokens within long context windows. DSA reduces API costs by approximately 50% while improving long-context performance and inference speed.
Mixture-of-Experts (MoE) Scale
Built on a 671B parameter architecture that activates only specialized expert subsets per inference. Combined with Engram memory and mHC stability, the MoE design enables efficient scaling while maintaining exceptional performance across diverse coding tasks.
DeepSeek V4 Performance Metrics
Comparative performance against industry-leading models
| Benchmark | DeepSeek V4 | Claude Opus | GPT-4 |
|---|---|---|---|
| HumanEval (Code Generation) | ~90%* | 88% | 82% |
| MMLU (Knowledge) | +3.4 pts vs MoE | - | - |
| BBH (Reasoning) | +5.0 pts vs MoE | - | - |
| Context Window | 1M+ tokens | 200K tokens | 128K tokens |
| API Cost Efficiency | 50% Reduction (DSA) | Standard | Standard |
*Performance metrics expected for Q1 2026 release. Benchmark comparisons based on industry sources and internal testing. Independent verification pending official launch.
Enterprise-Ready AI Development
Suitable for teams of all sizes and diverse application scenarios
Code Generation & Debugging
Generate production-ready code across multiple languages with context-aware suggestions. DeepSeek V4 understands entire project structures for intelligent code completion and real-time debugging assistance.
Repository-Level Bug Fixing
Diagnose and repair complex bugs spanning multiple files. Our 1M+ token context enables comprehensive stack trace analysis and cross-file dependency resolution that traditional tools cannot match.
Multi-File Project Analysis
Analyze entire codebases for architectural consistency, API interface validation, and import/export relationship tracking. Perfect for large-scale refactoring and technical debt reduction.
Private Deployment Options
Deploy DeepSeek V4 on your own infrastructure with open weights. Ideal for regulated industries requiring data sovereignty, including financial services, healthcare, and defense sectors.
Deploy DeepSeek V4 Today
Four simple steps to unlock the AI-driven development era
Choose Deployment Method
Integrate immediately via API or download open-source weights for local deployment on your infrastructure.
Configure Hardware
Recommended setup: Dual RTX 4090 or single RTX 5090. Supports new Blackwell GPU architecture for optimal performance.
Integrate & Deploy
Use our comprehensive SDK and documentation to integrate DeepSeek V4 into your development workflow and start coding smarter.
Scale & Optimize
Leverage quantization, batch processing, and DSA technology to optimize costs while maintaining exceptional performance.
About Hangzhou DeepSeek Artificial Intelligence
Hangzhou DeepSeek Artificial Intelligence is a leading Chinese AI research company dedicated to advancing open-source artificial intelligence for developers worldwide. Our mission is to democratize access to cutting-edge AI technology through innovative architecture design and cost-effective solutions.
Building on the success of DeepSeek-V3 and DeepSeek-R1, our research team has pioneered breakthrough technologies including Engram memory systems, mHC training stability, and GRPO reinforcement learning methods. We believe in the power of open collaboration and maintain our commitment to releasing model weights for community innovation.
DeepSeek V4 represents our most ambitious project, integrating years of research in memory architecture, sparse attention mechanisms, and massive-scale model training. Expected to launch in Q1 2026, DeepSeek V4 sets new standards for AI coding assistants through algorithmic innovation and efficient resource utilization.