DeepSeek: How a Chinese AI Lab Challenged ChatGPT for Just $5 Million

by | Mar 1, 2025 | Blog |

 

 

Introduction

DeepSeek has rapidly emerged as a significant player in the AI landscape, presenting a formidable challenge to established models like ChatGPT. What makes DeepSeek particularly remarkable is not just its performance, but how it achieved comparable results with significantly fewer resources than typical AI labs. This executive summary explores DeepSeek’s development, technical approach, and potential impact on the AI industry.

What is DeepSeek?

DeepSeek made headlines in December 2024 with the release of a 671-billion-parameter AI model that was trained for just $5.58 million—a fraction of what larger AI labs typically spend on model development. Despite these resource constraints, the model demonstrated performance rivaling GPT-4 and Claude 3.5 Sonnet in benchmarks.

More recently, DeepSeek introduced DeepSeek-R1, a model that excels specifically in mathematical and logical reasoning tasks. The company’s app has also gained significant traction, becoming the most downloaded free application on Apple’s App Store in the U.S.

DeepSeek launched a 671-billion-parameter AI model trained for just $5.58 million

DeepSeek vs. ChatGPT: A Technical Comparison

Feature ChatGPT (e.g., GPT-4) DeepSeek-R1
Architecture Transformer-based language models with billions of parameters Focused on reasoning tasks with a hybrid reward model
Training Data Diverse datasets from the internet, focusing on general-purpose tasks High-quality synthetic data with selective human post-processing
Fine-Tuning Reinforcement Learning with Human Feedback (RLHF) for alignment Iterative RL and Supervised Fine-Tuning (SFT) for improved reasoning capabilities
Reward Model Primarily neural-based, leveraging human-labeled data for feedback Combines rule-based (deterministic) and neural approaches
Accessibility Proprietary and commercialized, not fully open source Fully open-source, enabling broader experimentation and usage

DeepSeek’s app became the most downloaded free app on Apple’s App Store in the U.S.

Market & Strategy
Concerns & Theories
Key Techniques

Market & Strategic Implications ▼

Efficiency Revolution
DeepSeek demonstrates that high-performing AI can be developed with fewer resources, challenging prior cost assumptions. Cost-Effective
China's AI Progress
Despite U.S. GPU export restrictions, DeepSeek highlights China's significant progress in AI development. Competition
Market Disruption
Free high-quality models like DeepSeek are likely to drive down AI costs across the industry. Economics
Strategic Importance
There's a growing call for the U.S. to recognize AI leadership's strategic importance for economic and military dominance. Policy
The model reportedly demonstrates performance rivaling GPT-4 and Claude 3.5 Sonnet.

Conspiracy Theories & Concerns ▼

Government Backing
Suggestions of significant Chinese government support behind DeepSeek's rapid development. Funding
Data Privacy Risks
Concerns about potential transmission of U.S. user data to China. Security
Censorship Compliance
Reports indicate the model avoids sensitive topics, suggesting adherence to Chinese government censorship policies. Freedom
Development Skepticism
Some doubt the transparency and authenticity of DeepSeek's reported development process. Verification

Key Techniques in DeepSeek-R1 ▼

Chain of Thought (CoT) Reasoning
Prompts the model to "think out loud" and explain reasoning step-by-step, helping in self-evaluating mistakes and improving accuracy. Reasoning
Reinforcement Learning (RL)
DeepSeek uses Group Relative Policy Optimization (GRPO) to stabilize training and minimize drastic policy changes. Training
Model Distillation
Trains smaller models (e.g., Llama 3) using the larger DeepSeek-R1 model. These smaller models achieve similar performance at reduced computational costs. Efficiency

Conclusion

DeepSeek represents a significant milestone in AI development, demonstrating that competitive models can be created with substantially fewer resources than previously thought possible. While questions remain about its backing and development process, its technical achievements and market impact are undeniable. As AI development continues to accelerate globally, DeepSeek may well represent a turning point in how we approach building and deploying large language models.