
In January 2025, a Chinese AI lab called DeepSeek introduced two new AI models that have been making waves across the tech world. The most surprising part is how DeepSeek achieved incredible results using very limited resources compared to its competitors in the US. This has sparked a shift in the global AI race, where China is now seen as a major player, challenging the dominance of the United States.
The Rise of DeepSeek
For many years, the United States led the development of artificial intelligence, with big companies like OpenAI, Google, and Meta driving progress. However, DeepSeek’s latest AI models, particularly the DeepSeek-V3, are showing that China can now compete at a high level, even with restrictions on advanced hardware.
Here are some key points about DeepSeek’s breakthrough:
- DeepSeek-V3 was developed with just $5.6 million, much less than the $100 million that OpenAI spent on its GPT-4 model.
- The model was trained using older GPUs that are not as powerful as the latest ones used by US companies.
- Despite these challenges, DeepSeek-V3 has outperformed models like GPT-4 and Meta’s Llama in several benchmarks.
The Strategy Behind DeepSeek’s Success
DeepSeek’s success can be attributed to a few important factors:
- Using less advanced hardware, like H800 GPUs, DeepSeek employed innovative techniques to maximize their efficiency. This allowed them to get more from the resources they had.
- They also used smart designs like Multi-Head Latent Attention (MLA) and Mixture-of-Experts, which helped reduce the amount of computing power needed for training their models.
- DeepSeek’s approach proves that innovation doesn’t always require the best or most expensive technology, but rather creativity and resourcefulness.
DeepSeek’s Open-Source Approach, How to Use?
One of the most significant aspects of DeepSeek’s AI models is that they are open-source. This is in contrast to many US-based AI companies, such as OpenAI, which keep their models closed to the public. By making their AI available to everyone, DeepSeek is fostering global collaboration and allowing developers to build on and improve their models.
Here are some benefits of this open-source approach that any one can use it from the below github link:
- Anyone can access DeepSeek’s models (github link), refine them, and create new applications using them.
- This approach could lead to Chinese AI technology becoming embedded in the global tech ecosystem.
- It challenges the dominance of US-based companies and offers a new model for sharing AI resources.
The Global Impact of DeepSeek’s Innovation
DeepSeek’s success also raises some important questions about the future of AI and its implications on the global stage:
- As a Chinese company, DeepSeek’s AI models are influenced by Chinese regulations, which may limit their growth or how they are used in certain countries.
- Critics worry that AI systems developed under authoritarian governments may reflect biased or censored views. Concerns include how DeepSeek’s AI handles sensitive topics like Taiwan or the Tiananmen Square incident.
- The rise of Chinese AI models might prompt debates about whether AI should reflect democratic values or whether it will be shaped by government-controlled narratives.
The Future of AI: Will China Keep Rising?
With DeepSeek’s breakthrough, China is showing that it is no longer just a follower in the AI race, but a serious competitor. While the US still leads in many areas, the success of DeepSeek has demonstrated that resourcefulness and innovation can overcome challenges like limited access to the latest technology. The future of AI development might see even more collaboration across borders, but also more debates about ethics, control, and the role of government influence in shaping the future of technology.
Comparison of DeepSeek with other AI Models
Benchmark (Metric) | DeepSeek V3 | DeepSeek V2.5 | Qwen2.5 | Llama3.1 | Claude-3.5 | GPT-4o |
---|---|---|---|---|---|---|
Architecture | MoE | MoE | Dense | Dense | – | – |
# Activated Params | 37B | 21B | 72B | 405B | – | – |
# Total Params | 671B | 236B | 72B | 405B | – | – |
English MMLU (EM) | 88.5 | 80.6 | 85.3 | 88.6 | 88.3 | 87.2 |
MMLU-Redux (EM) | 89.1 | 80.3 | 85.6 | 86.2 | 88.9 | 88.0 |
MMLU-Pro (EM) | 75.9 | 66.2 | 71.6 | 73.3 | 78.0 | 72.6 |
DROP (3-shot F1) | 91.6 | 87.8 | 76.7 | 88.7 | 88.3 | 83.7 |
IF-Eval (Prompt Strict) | 86.1 | 80.6 | 84.1 | 86.0 | 86.5 | 84.3 |
GPQA-Diamond (Pass@1) | 59.1 | 41.3 | 49.0 | 51.1 | 65.0 | 49.9 |
SimpleQA (Correct) | 24.9 | 10.2 | 9.1 | 17.1 | 28.4 | 38.2 |
FRAMES (Acc.) | 73.3 | 65.4 | 69.8 | 70.0 | 72.5 | 80.5 |
LongBench v2 (Acc.) | 48.7 | 35.4 | 39.4 | 36.1 | 41.0 | 48.1 |
Code HumanEval-Mul (Pass@1) | 82.6 | 77.4 | 77.3 | 77.2 | 81.7 | 80.5 |
LiveCodeBench (Pass@1-COT) | 40.5 | 29.2 | 31.1 | 28.4 | 36.3 | 33.4 |
LiveCodeBench (Pass@1) | 37.6 | 28.4 | 28.7 | 30.1 | 32.8 | 34.2 |
Codeforces (Percentile) | 51.6 | 35.6 | 24.8 | 25.3 | 20.3 | 23.6 |
SWE Verified (Resolved) | 42.0 | 22.6 | 23.8 | 24.5 | 50.8 | 38.8 |
Aider-Edit (Acc.) | 79.7 | 71.6 | 65.4 | 63.9 | 84.2 | 72.9 |
Aider-Polyglot (Acc.) | 49.6 | 18.2 | 7.6 | 5.8 | 45.3 | 16.0 |
Math AIME 2024 (Pass@1) | 39.2 | 16.7 | 23.3 | 23.3 | 16.0 | 9.3 |
MATH-500 (EM) | 90.2 | 74.7 | 80.0 | 73.8 | 78.3 | 74.6 |
CNMO 2024 (Pass@1) | 43.2 | 10.8 | 15.9 | 6.8 | 13.1 | 10.8 |
Chinese CLUEWSC (EM) | 90.9 | 90.4 | 91.4 | 84.7 | 85.4 | 87.9 |
C-Eval (EM) | 86.5 | 79.5 | 86.1 | 61.5 | 76.7 | 76.0 |
C-SimpleQA (Correct) | 64.1 | 54.1 | 48.4 | 50.4 | 51.3 | 59.3 |
Summary of Key Points
- DeepSeek, a Chinese AI lab, introduced its breakthrough AI models, DeepSeek-V3 and DeepSeek-R1, in January 2025.
- The DeepSeek-V3 model was developed with just $5.6 million, far less than the billions spent by US companies like OpenAI and Google.
- DeepSeek used older generation GPUs to train its models, showcasing how creativity and resourcefulness can overcome hardware limitations.
- DeepSeek’s AI models have outperformed top models like GPT-4 and Meta’s Llama in several benchmarks, including coding and math tasks.
- DeepSeek uses innovative techniques like Multi-Head Latent Attention (MLA) and Mixture-of-Experts to reduce computing power requirements.
- The company’s open-source approach allows global developers to access, refine, and build on their AI models.
- This open-source strategy is in contrast to US companies that keep their AI models closed, enabling China to gain global influence in AI technology.
- Despite restrictions on advanced NVIDIA chips, DeepSeek has managed to create competitive AI models that challenge US dominance.
- DeepSeek’s success raises questions about whether AI systems developed by authoritarian governments could reflect biased or censored viewpoints.
- The rise of DeepSeek signifies China’s growing influence in the global AI race, potentially reshaping the future of AI technology.