What is DeepSeek AI?

In January 2025, the artificial intelligence landscape experienced a seismic shift when DeepSeek, a Chinese startup, launched its generative AI model that rivals tech giants like OpenAI, Meta, and Google, becoming the number one downloaded app in the US while being developed at a fraction of the cost of models like ChatGPT and Gemini. This breakthrough has been coined "AI's Sputnik moment" in the global race to harness the power of AI, fundamentally challenging assumptions about the resources required to develop cutting-edge artificial intelligence.

Whether you're an AI enthusiast, developer, business owner, or simply curious about the latest technological advancements, understanding DeepSeek is essential in 2025. This comprehensive guide will explore what DeepSeek is, how it works, its key features, and why it's disrupting the AI industry.

DeepSeek is a Chinese artificial intelligence company that develops large language models (LLMs), headquartered in Hangzhou, Zhejiang, and is owned and funded by the Chinese hedge fund High-Flyer. The company was founded in July 2023 by Liang Wenfeng, the co-founder of High-Flyer, who also serves as CEO for both companies.

DeepSeek's primary mission focuses on developing open-source AI models that are both powerful and cost-effective. Unlike many AI companies that prioritize commercial applications, DeepSeek has stated that it focuses on research and does not have immediate plans for commercialization, allowing the company to push boundaries without the pressure of immediate monetization.

What sets DeepSeek apart from competitors like OpenAI, Google, and Anthropic is its approach to AI development. While AI development has long been a game of brute force—bigger models, more computing power, and cutting-edge chips—DeepSeek took a different approach, proving that powerful AI can be built through smarter software and hardware optimization.

DeepSeek has released several groundbreaking models, each serving different purposes and showcasing various innovations in AI technology.

DeepSeek-V3 is a strong Mixture-of-Experts (MoE) language model with 671 billion total parameters with 37 billion activated for each token, achieving efficient inference and cost-effective training through Multi-head Latent Attention (MLA) and DeepSeekMoE architectures.

Key Features of DeepSeek-V3:

• Massive Scale with Efficiency: While the model has 671 billion parameters total, only 37 billion are active per token, dramatically reducing computational requirements
• Extended Context Length: Supports up to 128,000 tokens, enabling processing of extremely long documents and conversations
• Cost-Effective Training: The company claims it trained its V3 model for $6 million—far less than the $100 million cost for OpenAI's GPT-4 in 2023—using approximately one-tenth the computing power consumed by Meta's comparable model, Llama 3.1
• Advanced Training Techniques: Uses FP8 mixed precision training framework, auxiliary-loss-free strategy for load balancing, and multi-token prediction training objectives

DeepSeek launched the DeepSeek chatbot alongside its DeepSeek-R1 model in January 2025, released under the MIT License, providing responses comparable to other contemporary large language models such as OpenAI's GPT-4 and o1.

What Makes R1 Special:

• Pure Reinforcement Learning: DeepSeek-R1-Zero, trained via large-scale reinforcement learning without supervised fine-tuning as a preliminary step, demonstrated remarkable performance on reasoning, naturally emerging with capabilities such as self-verification, reflection, and generating long chains of thought
• Advanced Reasoning Capabilities: Excels at mathematical problem-solving, coding challenges, and complex logical reasoning tasks
• Competitive Performance: DeepSeek-R1 achieves performance comparable to OpenAI-o1 across math, code, and reasoning tasks
• Open Source Philosophy: Released under MIT License, allowing researchers and developers to freely use, modify, and deploy the model

On August 21, 2025, DeepSeek released DeepSeek V3.1 under the MIT License, featuring a hybrid architecture with thinking and non-thinking modes, surpassing prior models like V3 and R1 by over 40% on certain benchmarks like SWE-bench and Terminal-bench.

The most recent iteration, V3.2-Exp released on September 29, 2025, uses DeepSeek Sparse Attention (DSA), which makes the AI better at handling long documents and conversations while cutting the cost of running the AI in half compared to the previous version.

DeepSeek-Coder-V2, released in July 2024, is a 236 billion-parameter model offering a context window of 128,000 tokens, designed for complex coding challenges. This specialized model caters specifically to software developers, offering enhanced performance on programming tasks, code generation, and debugging.

Understanding the technical innovations behind DeepSeek helps explain why it's so revolutionary in the AI space.

DeepSeek's model doesn't activate all its parameters at once like GPT-4. Instead, it uses a technique called Mixture-of-Experts (MoE), which works like a team of specialists rather than a single generalist model. When asked a question, only the most relevant parts of the AI "wake up" to respond, while the rest stay idle.

This architectural decision provides several advantages:

• Reduced Computational Costs: Only necessary components are active for each query
• Improved Efficiency: Faster response times without sacrificing quality
• Scalability: Easier to expand capabilities without proportional increases in resource requirements
• Specialized Performance: Different "experts" can be optimized for specific tasks

One of DeepSeek's most significant achievements is demonstrating that cutting-edge AI doesn't require the most expensive hardware.

DeepSeek designed their model to work on Nvidia H800 GPUs—less powerful but more widely available than the restricted H100/A100 chips, which are also much cheaper. They used PTX, an assembly-like programming method that lets developers control how AI interacts with the chip at a lower level, allowing them to squeeze more performance out of less powerful hardware.

Training was optimized to reduce expensive human fine-tuning. Most AI models, including GPT-4, rely on large teams of human reviewers to manually refine responses. DeepSeek automated much of this process using reinforcement learning, meaning the AI learns more efficiently from experience rather than requiring constant human oversight.

DeepSeek's implementation of Multi-Head Latent Attention is another technical innovation that sets it apart. MLA introduces compressed latent vectors to reduce the Key-Value cache size, significantly decreasing memory usage during inference while maintaining model performance. This optimization is particularly important for maintaining efficiency when processing long contexts.

DeepSeek offers a comprehensive suite of features that make it versatile for various applications.

1. Advanced Reasoning and Problem-Solving

DeepSeek excels at tasks requiring logical inference and step-by-step reasoning. The R1 model particularly shines in mathematical proofs, complex decision-making, and analytical tasks where transparency in the reasoning process is crucial.

**2. Coding and Development**

With specialized models like DeepSeek-Coder, the platform provides exceptional support for software development, including:
- Code generation and completion
- Bug detection and debugging assistance
- Code explanation and documentation
- Multi-language programming support
- Algorithm optimization suggestions

**3. Content Creation and Writing**
DeepSeek can help write content, edit and improve grammar or style, and generate ideas for social media posts and marketing campaigns. The model understands context, maintains consistent tone, and produces high-quality written content across various formats.

**4. Data Analysis and Insights**
The model can analyze data, identify trends, and generate relevant insights; it can propose how to present data and automate repetitive tasks. This makes DeepSeek valuable for business intelligence, research analysis, and data-driven decision-making.

**5. Project Management and Organization**
DeepSeek can create to-do lists, set priorities, and track progress; it can also summarize meetings, take notes, and draft communication for teams, serving as an AI-powered project management assistant.

**6. Learning and Educational Support**
DeepSeek can help create guides, tutorials, and explanations on how to use different tools, as well as assist in translating or learning languages. The model's ability to explain complex concepts in simple terms makes it an excellent educational companion.

**Think vs. Non-Think Modes**
DeepSeek V3.1 introduced a hybrid architecture with two distinct operational modes:
- **Think Mode**: Encourages internal chain-of-thought reasoning, showing its work and logical steps
- **Non-Think Mode**: Provides faster, more direct responses when speed is prioritized over detailed reasoning

This flexibility allows users to choose between thoroughness and efficiency based on their specific needs.

**Long Context Processing**
With support for up to 128,000 tokens, DeepSeek can process entire books, lengthy research papers, or extensive codebases in a single context window. The recent introduction of DeepSeek Sparse Attention makes the AI better at handling long documents and conversations, further improving this capability.

**Function Calling and JSON Output**
The R1-0528 model supports system prompts, JSON output and function calling, making it more suitable for agentic AI use cases. This enables seamless integration with other software systems and automated workflows.

DeepSeek offers flexibility in how users can access and interact with its AI models.

### Official DeepSeek Platforms

1. **Web Interface**: Direct access through the official DeepSeek website (deepseek.com)
2. **Mobile Applications**: Available for both iOS and Android devices
3. **API Access**: Developer-friendly API for integration into applications and services
4. **Open Source Models**: Full model weights available under MIT License for self-hosting

### DeepSeek Pricing and Cost Efficiency

One of DeepSeek's most compelling advantages is its cost structure. The platform offers:
- **Free Tier**: Basic access to chat functionality
- **Significantly Lower API Costs**: API pricing was cut by more than 50% in many cases with the V3.2-Exp release
- **Context Caching**: Stores repeated input tokens at lower costs for multi-turn conversations
- **Operational Efficiency**: Estimated operational expenses at only 15%-50% of comparable models like OpenAI's o1

### Experience DeepSeek Through Chat Smith

For users looking for a unified AI experience across multiple platforms, Chat Smith offers an excellent solution. Chat Smith is an advanced AI chatbot that integrates APIs from leading AI providers including ChatGPT, Gemini, DeepSeek, and Grok, allowing you to:

- **Compare Model Responses**: See how different AI models approach the same question
- **Switch Between Models Seamlessly**: Choose the best model for each specific task
- **Leverage DeepSeek's Reasoning Power**: Access DeepSeek's advanced reasoning capabilities alongside other leading models
- **Cost-Effective Multi-Model Access**: Utilize DeepSeek's efficient pricing through a single, unified interface
- **Enhanced Flexibility**: Select DeepSeek for complex reasoning tasks, ChatGPT for conversational AI, Gemini for multimodal needs, or Grok for real-time information

By consolidating multiple AI models in one platform, Chat Smith empowers users to leverage the unique strengths of each model, including DeepSeek's exceptional reasoning capabilities and cost efficiency, without the need to manage multiple separate subscriptions and interfaces.

Understanding DeepSeek's position in the competitive AI landscape is crucial for making informed decisions about which AI model to use.

**Performance:**
- DeepSeek R1 achieves comparable performance to GPT-4 and o1 on reasoning tasks
- ChatGPT maintains slight advantages in conversational fluency and general knowledge
- DeepSeek excels particularly in mathematical reasoning and coding challenges

**Cost:**
- DeepSeek offers significantly lower API pricing (50-85% lower in many cases)
- ChatGPT has more established enterprise support and SLA guarantees
- DeepSeek's open-source nature provides free self-hosting options

**Accessibility:**
- ChatGPT has broader global availability and established user base
- DeepSeek faces restrictions in some countries due to data privacy concerns
- DeepSeek offers more transparent model architecture due to open-source approach

**Technical Approach:**
- Gemini focuses on multimodal capabilities (text, image, video, audio)
- DeepSeek specializes in text-based reasoning and code generation
- Gemini integrates deeply with Google's ecosystem and services
- DeepSeek prioritizes efficiency and cost-effectiveness

**Use Cases:**
- Gemini: Better for multimodal tasks, Google Workspace integration, and diverse content types
- DeepSeek: Superior for mathematical reasoning, complex coding, and cost-sensitive applications

**Reasoning Capabilities:**
- Both models excel at complex reasoning and analytical tasks
- Claude emphasizes helpful, harmless, and honest principles
- DeepSeek focuses on pure reasoning performance through reinforcement learning
- Claude offers stronger safety features and content moderation

**Development Philosophy:**
- Claude: Proprietary model with focus on AI safety
- DeepSeek: Open-source approach encouraging research and experimentation

**Positioning:**
- Grok focuses on real-time information and Twitter/X integration
- DeepSeek emphasizes reasoning, mathematics, and coding
- Grok has access to current events through X platform
- DeepSeek offers open-source models and lower costs

Several technical innovations enable DeepSeek's remarkable efficiency and performance.

DeepSeek's approach to reinforcement learning represents a significant departure from traditional methods. The Group Relative Policy Optimization (GRPO) technique used by DeepSeek doesn't require a separate critic model, instead estimating baselines from group scores. This reduces complexity and training time while maintaining or improving performance.

DeepSeek-V3 pioneers an auxiliary-loss-free strategy for load balancing, which minimizes the performance degradation that arises from encouraging load balancing. This ensures that different experts in the MoE architecture are utilized efficiently without compromising model quality.

For the first time, DeepSeek validated the feasibility and effectiveness of FP8 training on an extremely large-scale model. Using 8-bit floating-point numbers instead of standard 32-bit significantly reduces memory requirements and computational costs without substantially impacting model performance.

DeepSeek-V3 sets a multi-token prediction training objective for stronger performance, which can also be used for speculative decoding for inference acceleration. This allows the model to predict multiple tokens simultaneously, improving both training efficiency and inference speed.

Through co-design of algorithms, frameworks, and hardware, DeepSeek overcame communication bottlenecks in cross-node MoE training, nearly achieving full computation-communication overlap. This dramatically enhances training efficiency, especially at scale.

The versatility of DeepSeek makes it suitable for numerous real-world applications across various industries.

**Code Generation and Review:**
- Automated code generation from natural language descriptions
- Code review and quality assurance
- Refactoring suggestions and optimization recommendations
- Documentation generation

**Debugging and Problem-Solving:**
- Identifying bugs and suggesting fixes
- Performance optimization
- Security vulnerability detection
- Test case generation

**Mathematical Research:**
- Proof verification and generation
- Complex calculations and symbolic mathematics
- Statistical analysis and modeling
- Algorithm development

**Research Assistance:**
- Literature review and summarization
- Hypothesis generation
- Experimental design suggestions
- Data analysis and interpretation

**Data Analytics:**
- Business intelligence and trend analysis
- Predictive modeling
- Customer behavior analysis
- Market research synthesis

**Process Automation:**
- Workflow optimization
- Document processing and generation
- Report creation and summarization
- Customer service automation

**Personalized Tutoring:**
- Adaptive learning paths
- Concept explanation at appropriate complexity levels
- Practice problem generation
- Progress tracking and feedback

**Content Creation:**
- Educational material development
- Interactive learning experiences
- Assessment question generation
- Language learning assistance

**Writing Assistance:**
- Blog posts and articles
- Marketing copy
- Technical documentation
- Creative storytelling

**Content Optimization:**
- SEO optimization
- Style and tone adjustment
- Grammar and clarity improvement
- Multi-language translation

As with any AI technology, especially one developed internationally, understanding security and privacy implications is crucial.

DeepSeek has faced scrutiny regarding data handling practices. Several countries including Taiwan, Australia, Italy, the United States, and South Korea have banned government agencies from using DeepSeek, citing national security concerns.

**Key Privacy Considerations:**
- Data residency and storage location
- Information sharing policies
- Compliance with local data protection regulations (GDPR, CCPA, etc.)
- User data anonymization practices

The R1-0528 model has been noted for more tightly following official Chinese Communist Party ideology and censorship in its answers to questions than prior models. Organizations must consider:
- Content filtering practices
- Political and cultural sensitivities
- Transparency in content moderation
- Impact on research and development

The CAISI evaluation notes that DeepSeek models' shortcomings related to security and censorship of model responses may pose a risk to application developers, consumers, and US national security.

**Security Aspects to Consider:**
- API security and authentication
- Model vulnerability to adversarial attacks
- Data encryption in transit and at rest
- Third-party audit and verification

Organizations using DeepSeek should:
- Conduct thorough risk assessments
- Implement appropriate governance frameworks
- Ensure compliance with applicable regulations
- Maintain transparency with stakeholders about AI usage

DeepSeek's emergence has implications far beyond the AI industry, affecting geopolitics, economics, and technological development worldwide.

On January 27, DeepSeek launched its model and its AI assistant became the number one downloaded app in the US, surprising an industry that assumed only big Western companies could dominate AI. Many AI-related stocks, including Nvidia, took a hit as investors reevaluated the competitive landscape.

**Economic Impact:**
- Stock market volatility in AI-related companies
- Reevaluation of AI hardware requirements and investments
- Disruption of established pricing models
- Acceleration of open-source AI development

The evaluation from CAISI responds to President Donald Trump's America's AI Action Plan, which directs CAISI to conduct research and publish evaluations of frontier models from the PRC. DeepSeek has intensified:
- US-China AI competition
- Export control debates on AI chips
- International collaboration challenges
- Concerns about AI sovereignty

DeepSeek's cost-efficient approach and open-source philosophy are democratizing access to advanced AI:
- Lowering barriers to entry for startups and researchers
- Enabling developing countries to participate in AI advancement
- Reducing dependency on expensive proprietary models
- Accelerating AI innovation through open collaboration

DeepSeek is influencing how the industry thinks about:
- Resource efficiency in AI development
- Open-source versus proprietary models
- Training methodology innovations
- Cost-effective scaling strategies

While DeepSeek represents significant technological advancement, it's important to understand its limitations.

**Performance Gaps:**
- CAISI evaluation found that AI models from DeepSeek lag behind US models in performance
- Occasional hallucinations and accuracy issues
- Language mixing in certain contexts
- Readability challenges in some outputs

**Resource Requirements:**
- Despite efficiency gains, large models still require substantial computational resources for self-hosting
- Smaller distilled models sacrifice some performance for accessibility
- Context processing can be slow for very long documents

**Service Reliability:**
- Popularity has led to outages and service disruptions
- Reports of cyber-attacks on infrastructure
- Scaling challenges with rapid user growth

**Integration Complexity:**
- Learning curve for optimal prompt engineering
- Configuration requirements for best performance
- Compatibility with existing systems and workflows

**Geographic Restrictions:**
- Government bans in several countries
- Corporate policy restrictions
- Compliance challenges in regulated industries

**Trust and Acceptance:**
- Concerns about data handling and privacy
- Content moderation transparency
- Political and ideological considerations

Looking ahead, several developments are shaping DeepSeek's trajectory.

### Upcoming Features and Models

DeepSeek is developing an artificial intelligence model with more advanced AI agent features to compete with US rivals like OpenAI, designed to carry out multi-step actions on a person's behalf with minimal direction from the user, also meant to learn and improve based on its prior actions.

**Expected Developments:**
- Enhanced multimodal capabilities (vision, audio)
- Improved agent and tool-using abilities
- Further cost reductions and efficiency gains
- Expanded language support and cultural adaptation

### Research Directions

Recent innovations like DeepSeek's OCR model that uses visual tokens instead of text tokens to pack written information into image form, allowing the model to retain nearly the same information while using far fewer tokens, suggest exciting research directions:

- Novel memory and context management approaches
- Advanced reasoning techniques
- Hardware-software co-design
- Efficient training methodologies

### Industry Influence

DeepSeek's impact on the broader AI industry will likely include:
- Acceleration of open-source AI development
- Renewed focus on efficiency and cost-effectiveness
- Innovation in training methodologies
- Pressure on proprietary model providers to reduce costs

The AI landscape will continue evolving with:
- Increased collaboration between open-source projects
- Competition driving innovation across all providers
- Cross-pollination of techniques and approaches
- Emergence of hybrid commercial-open-source models

To maximize the value of DeepSeek, consider these best practices.

**For Reasoning Tasks:**
- Include explicit instructions for step-by-step reasoning
- Use phrases like "Please reason step by step"
- For mathematical problems, request answers in specific formats (e.g., "put your final answer within \boxed{}")
- Set temperature between 0.5-0.7 for optimal balance

**For Coding Tasks:**
- Provide clear requirements and constraints
- Specify programming language and version
- Include example inputs and expected outputs
- Request explanations alongside code

**General Guidelines:**
- Avoid using system prompts (include all instructions in user prompts)
- Be specific about desired output format
- Provide relevant context upfront
- Use clear, concise language

**Choose DeepSeek R1 when:**
- Advanced reasoning is required
- Mathematical or logical problem-solving is needed
- Transparency in reasoning process is important
- Cost efficiency is a priority

**Choose DeepSeek V3 when:**
- General language understanding tasks
- Conversational applications
- Content generation
- Faster response time is preferred

**Choose DeepSeek-Coder when:**
- Software development projects
- Code review and optimization
- Debugging assistance
- Programming education

### Integration Approaches

**API Integration:**
- Implement proper error handling and retries
- Use context caching for repeated queries
- Monitor usage and costs
- Implement rate limiting

**Self-Hosting:**
- Assess hardware requirements carefully
- Consider distilled models for resource-constrained environments
- Implement proper security measures
- Plan for scaling and updates

**Hybrid Approaches:**
- Use Chat Smith or similar platforms for multi-model access
- Route queries to appropriate models based on task type
- Implement fallback mechanisms
- Conduct regular performance comparisons

1. What is DeepSeek AI?

DeepSeek is a Chinese artificial intelligence company founded in July 2023 that develops open-source large language models. It gained global attention in January 2025 by releasing the DeepSeek-R1 model, which achieves performance comparable to leading AI models like ChatGPT while being developed at a fraction of the cost.

2. Is DeepSeek really cheaper than ChatGPT?

Yes, DeepSeek offers significantly lower costs compared to ChatGPT. The company claims to have trained its models for approximately $6 million compared to $100 million for GPT-4. API pricing is 50-85% lower than comparable services, and the open-source nature allows for free self-hosting, though this requires substantial technical expertise and computational resources.

3. How does DeepSeek achieve such efficiency?

DeepSeek achieves efficiency through several innovations: using a Mixture-of-Experts architecture that activates only necessary parameters, optimizing for less expensive H800 GPUs instead of top-tier chips, implementing FP8 mixed precision training, using advanced load balancing strategies, and automating much of the training process through reinforcement learning rather than expensive human fine-tuning.

4. Can I use DeepSeek for commercial purposes?

Yes, DeepSeek models are released under the MIT License, which permits commercial use, modification, and distribution. However, users should review the specific license terms, consider data privacy implications, and ensure compliance with applicable regulations in their jurisdiction.

5. Is DeepSeek safe and secure to use?

DeepSeek's safety and security depend on your specific use case and risk tolerance. Government evaluations have identified potential security shortcomings and content censorship concerns. Several countries have banned government use of DeepSeek due to national security considerations. Organizations should conduct thorough risk assessments, implement appropriate security measures, and consider data sensitivity before deployment.

6. What are the main differences between DeepSeek R1 and DeepSeek V3?

DeepSeek R1 is specifically optimized for reasoning tasks, using reinforcement learning to develop advanced logical inference capabilities, chain-of-thought reasoning, and self-verification. DeepSeek V3 is a more general-purpose model focused on efficient language understanding and generation. R1 is better for mathematical problems and complex reasoning, while V3 is better for conversational AI and general tasks.

7. Can DeepSeek replace ChatGPT in my workflow?

DeepSeek can replace ChatGPT for many use cases, particularly those involving mathematical reasoning, coding, and cost-sensitive applications. However, ChatGPT may still have advantages in conversational fluency, general knowledge, broader geographic availability, and established enterprise support. Consider using platforms like Chat Smith that provide access to multiple AI models to leverage the strengths of each.

8. What programming languages does DeepSeek support?

DeepSeek, particularly DeepSeek-Coder, supports all major programming languages including Python, JavaScript, Java, C++, C#, Go, Rust, PHP, Ruby, Swift, Kotlin, and many others. The model has been trained on diverse code repositories and can handle code generation, debugging, and explanation across different languages and frameworks.

9. How do I access DeepSeek?

You can access DeepSeek through multiple channels: the official website (deepseek.com) for web-based chat, mobile apps for iOS and Android, API access for developers integrating into applications, or by downloading and self-hosting the open-source model weights. Additionally, platforms like Chat Smith provide unified access to DeepSeek alongside other leading AI models.

10. What is the context window size for DeepSeek?

DeepSeek models support context windows of up to 128,000 tokens, allowing them to process extremely long documents, entire codebases, or lengthy conversations in a single context. The recent DeepSeek Sparse Attention (DSA) innovation further improves efficiency when handling very long contexts.

11. Does DeepSeek support multiple languages?

Yes, DeepSeek supports multiple languages, though performance may vary across different languages. The model has been trained on multilingual data and can understand and generate content in major world languages. However, like most AI models, it typically performs best in English and may have varying levels of proficiency in other languages.

12. What are the hardware requirements for running DeepSeek locally?

Running full DeepSeek models locally requires significant computational resources, typically multiple high-end GPUs (Nvidia H800, H100, or A100 series). However, DeepSeek offers distilled versions with smaller parameter counts (1.5B to 70B) that can run on more modest hardware, including high-end consumer GPUs for the smallest versions.

13. How does DeepSeek handle data privacy?

DeepSeek's data privacy practices have raised concerns, leading to government bans in several countries. Users should review DeepSeek's privacy policy, understand data storage and processing locations, consider applicable data protection regulations, and implement additional privacy measures when handling sensitive information. For highly sensitive data, consider self-hosting options or alternative models with clearer privacy guarantees.

14. Can DeepSeek generate images or work with multimedia?

As of November 2025, DeepSeek primarily focuses on text-based tasks. While the company has developed models like DeepSeek-VL with visual capabilities and has demonstrated innovations in image-based token processing, mainstream multimodal capabilities remain more limited compared to models like GPT-4V or Gemini. However, this is an active area of development.

15. What is the difference between DeepSeek's Think and Non-Think modes?

Think Mode encourages the model to show its reasoning process through chain-of-thought, providing transparency in how it arrives at conclusions—ideal for complex problems requiring verification. Non-Think Mode provides faster, more direct responses without showing intermediate reasoning steps—suitable for straightforward queries where speed is prioritized. Users can choose based on whether they need to understand the model's reasoning process.

DeepSeek represents a watershed moment in artificial intelligence development, demonstrating that cutting-edge AI performance doesn't necessarily require the massive resources previously thought essential. By developing their AI model at a fraction of the cost of models like ChatGPT and Gemini, DeepSeek challenged fundamental assumptions about AI development.

Whether you're a developer, researcher, business leader, or AI enthusiast, understanding and potentially leveraging DeepSeek is increasingly important in 2025's AI landscape. The model's combination of performance, efficiency, and accessibility makes it a compelling option for many use cases, while its limitations and concerns require careful consideration.

The AI revolution continues to unfold, and DeepSeek has proven that innovation, efficiency, and accessibility can coexist in ways that challenge conventional wisdom. As we move forward, the lessons learned from DeepSeek's approach will likely influence AI development for years to come, regardless of which models ultimately dominate the market.

Ready to experience DeepSeek alongside other leading AI models? Try Chat Smith today and discover how multi-model AI access can transform your workflow, combining DeepSeek's cost-efficient reasoning power with the unique strengths of ChatGPT, Gemini, and Grok in one seamless platform.