DeepSeek: Complete Capabilities Cheatsheet (April 2025)
Best Features to Master
Advanced Reasoning (DeepSeek-R1)
What it does: Provides sophisticated problem-solving through reinforcement learning
Key capabilities:
- Multi-step reflection with visible chain-of-thought reasoning
- Self-verification and correction of problem-solving approaches
- Uses thinking tags (
<think>\n\n</think>) to show reasoning process - Automatically allocates more thinking time to complex problems
Best for: Mathematics, multi-step logical problems, complex coding tasks
Mixture-of-Experts (MoE) Architecture
What it does: Delivers high performance with drastically reduced computational costs
Key capabilities:
- Activates only relevant neural sub-networks per query
- Reduces compute costs by up to 90% versus traditional models
- Fine-grained expert segmentation with shared expert isolation
- DeepSeek-V2: 236 billion total parameters with only 21 billion activated per token
Best for: Enterprise deployment, cost-sensitive applications, efficiency-focused use cases
Cost-Effective Performance
What it does: Provides top-tier AI capabilities at fraction of competitor costs
Key capabilities:
- API pricing at $0.01/M input tokens (vs $30/M for competitors)
- Inference costs at approximately 2% of equivalent OpenAI outputs
- Intelligent caching system ($0.14/million tokens for cache hits)
- Runs on more accessible hardware configurations
Best for: Startups, research organizations, high-volume applications
Open-Source Accessibility
What it does: Offers full commercial use permissions with model weights
Key capabilities:
- MIT License allowing modification and commercial use
- Full model weights available for download and adaptation
- Multiple model sizes (1.5B to 70B parameters) for different needs
- Available through web platform and API
Best for: Custom AI development, research, specialized applications
When exploring DeepSeek's advanced reasoning capabilities, try using the <think> tags explicitly in your prompts to see the model's chain-of-thought reasoning process in action. This is especially helpful for debugging complex problem-solving approaches.
Model Variants
DeepSeek-R1 Series
- DeepSeek-R1-Zero: Pure RL-trained model without human-annotated data
- DeepSeek-R1 (Hybrid): Multi-stage training combining RL with cold-start data
- DeepSeek-R1-Distill-Qwen-32B: Distilled model outperforming OpenAI-o1-mini
DeepSeek LLM Series
- DeepSeek LLM 67B: 67B parameter model trained on 2 trillion tokens
- DeepSeek LLM 7B: Compact 7B parameter model for efficient deployment
MoE Models
- DeepSeek-MoE 16B: 16.4B parameter MoE model with performance of larger models
- DeepSeek-V2: Advanced MoE model with 128K token context window
Model Selection Guide
Choose the right model for your specific needs:
- For maximum reasoning power: DeepSeek-R1 (Hybrid)
- For cost-efficiency at scale: DeepSeek-MoE 16B
- For edge devices: DeepSeek LLM 7B
- For enterprise deployments: DeepSeek-V2
Technical Specifications
Model Architecture
- Training Tokens: 14.8 trillion (3x GPT-4's dataset)
- Context Window: 128K tokens for processing large documents
- Response Speed: 67ms latency (2x faster than o3-mini)
- Coding Accuracy: 63.8% on SWE-Bench (matching GPT-4.5)
Benchmark Performance
DeepSeek's Codeforces Elo rating of 2,029 outperforms 96.3% of human participants in competitive programming contests, placing it in the top 4% of all competitors.
Specialized Capabilities
Multilingual & Multimodal
What it does: Processes multiple languages and modalities
Key capabilities:
- Strong performance in both English and Chinese
- Supports 200+ languages
- DeepSeek-VL2 series integrates vision and language processing
- Dynamic tiling vision encoding for high-resolution images
Best for: International applications, image analysis, cross-modal tasks
Coding Excellence
What it does: Generates, analyzes, and optimizes code at a professional level
Key capabilities:
- Builds full-stack applications from single prompts
- Enterprise-grade code generation
- Strong performance on coding benchmarks
- Advanced debugging and optimization
Best for: Software development, code review, algorithm implementation
Enterprise Applications
What it does: Provides specialized solutions for business needs
Key capabilities:
- Real-time data processing (handles 500M daily queries)
- Supply chain optimization (predicts disruptions with 89% accuracy)
- Financial forecasting (processes 10K+ page reports in minutes)
- E-commerce visual search (90% accuracy in product matching)
Best for: Business intelligence, operational optimization, analytics
Integration Highlight
DeepSeek's multimodal capabilities allow for seamless processing of text, images, and structured data in a single API call, making it ideal for complex business intelligence dashboards and document analysis workflows.
Access Options
Web Platform
- Free tier with daily cap of 50 messages
- DeepSeek Chat platform for direct interaction
- No subscription requirement
API Access
- Pay-per-use pricing model
- Significantly lower costs than competitors
- Enterprise-grade reliability
- Integration options for various applications
Open-Source Deployment
- Self-hosted options with full model weights
- Customization and fine-tuning possibilities
- Commercial use permissions under MIT License
- Options for various hardware configurations
For a typical enterprise deployment processing 100M tokens daily:
- OpenAI GPT-4: ~$3,000/day
- Anthropic Claude: ~$2,200/day
- DeepSeek-V2: ~$60/day
Practical Applications
Technical Problem-Solving
How to use it:
- Enable chain-of-thought reasoning for complex problems
- Use thinking tags to see reasoning process
- Request step-by-step solutions
- Provide detailed context for best results
Best for: Mathematics, science, engineering, complex logic
Research & Development
How to use it:
- Leverage 128K context window for comprehensive analysis
- Process large academic papers and datasets
- Request comparative analysis across multiple sources
Best for: Scientific research, academic analysis, innovation
Specialized Domains
How to use it:
- Fine-tune for specific domains like medical reasoning
- Request domain-specific analysis and insights
- Apply to logic-heavy tasks requiring expert reasoning
Best for: Healthcare, finance, legal analysis, specialized fields
Consumer Applications
How to use it:
- Smart home integration for predictive automation
- Personalized education adapting to individual learning styles
- Content generation and analysis
Best for: Personal assistance, education, content creation
Application Example: Supply Chain Optimization
A global manufacturing company implemented DeepSeek's MoE model to:
- Process 10+ years of supply chain data (2TB)
- Identify 127 previously unknown risk factors
- Reduce production disruptions by 32%
- Save $4.2M annually in logistics costs
All while running on existing hardware infrastructure with minimal additional costs.
Pro Tips
Optimizing Performance
- Use temperature settings between 0.5-0.7 for controlled creativity
- Enable "Expert Mode" for technical problem-solving
- Request explicit reasoning paths for complex problems
- Leverage caching system for frequently accessed content
Cost Efficiency
- Use smaller distilled models for simpler tasks
- Implement intelligent caching for repetitive queries
- Balance context window usage for optimal token efficiency
- Consider batch processing for large-scale tasks
Development Integration
- Explore multi-agent support for coordinated tasks
- Chain multiple API calls for complex workflows
- Implement feedback loops for continuous improvement
- Experiment with different model variants for specific use cases
For mathematical problem solving:
Try this prompt pattern:
I need to solve this problem: [problem description] Please use <think> tags to show your reasoning process. Think step-by-step and verify each step before moving to the next. If you encounter an issue, backtrack and try a different approach.
Strengths & Limitations
Strengths
- Unmatched cost efficiency (GPT-4 level performance at 1/18th cost)
- Open-source accessibility with full commercial permissions
- Advanced reasoning capabilities through reinforcement learning
- Strong multilingual support, especially for Chinese
Limitations
- Regional restrictions and potential legal challenges
- Occasional stability issues during peak usage
- Struggles with abstract philosophy and creative tasks
- Less mature ecosystem compared to established competitors
When to Choose DeepSeek
DeepSeek is the ideal choice when:
- Cost-efficiency is a primary concern
- You need strong reasoning capabilities for technical problems
- Self-hosting or model customization is required
- Your use case involves mathematical reasoning or coding
- You need both English and Chinese language support
Consider alternatives for creative writing, philosophical discussions, or when a more mature ecosystem is needed.