In an era where artificial intelligence is redefining the boundaries of technology, DeepSeek is emerging as a pioneer in AI model training transformation. Embracing innovation and promoting transparency, the company offers a free, open-source tool that operates both locally on a computer and through a chat application, boasting computing power comparable to GPT.
Benchmark data show that DeepSeek-R1 achieves results comparable to leading models such as OpenAI, while surpassing them in terms of cost and hardware efficiency.
For example, in the Codeforces and MATH-500 tests, DeepSeek achieved 96.3% and 97.3% accuracy, respectively, making it a leader in the field of natural language processing. However, on the evening of January 27, 2025, the Chinese technology giant Alibaba presented the Qwen 2.5-Max model, which, according to initial tests, may surpass DeepSeek and OpenAI in terms of analytical capabilities and contextual understanding. This model has been announced as the future of AI, ready for even more advanced tasks.
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Key achievements of DeepSeek
DeepSeek has revolutionized the approach to training language models by reducing costs, hardware requirements, and data processing time. Here are the most significant innovations and their impact:- Lowering Model Training Costs: DeepSeek has transformed the cost structure of training language models, reducing expenses from $100 million to just $5 million. This breakthrough makes advanced AI technology accessible even to smaller organizations.
- Reducing Hardware Requirements: The company has significantly lowered GPU demand from 100,000 to just 2,000, greatly lowering the entry barriers for AI development teams.
- Innovative Approach to Computational Precision: DeepSeek employs lower-precision calculations (8-bit instead of the standard 32-bit), reducing memory usage by up to 75% while accelerating model performance without significantly compromising accuracy.
- Multi-Token System: This innovation enables the processing of entire phrases instead of individual words, doubling the model’s speed while maintaining 90% precision.
- Expert Module System: DeepSeek has introduced a system of specialized modules that activate only when needed. This approach maximizes efficiency and optimizes resource utilization.
- Open Source: All of DeepSeek’s technology is open and accessible to everyone. This strategic decision strengthens collaboration within the global AI community.
Comparison of DeepSeek with competitors
Benchmark data show that DeepSeek-R1 achieves results comparable to leading models such as OpenAI, while surpassing them in terms of cost and hardware efficiency.For example, in the Codeforces and MATH-500 tests, DeepSeek achieved 96.3% and 97.3% accuracy, respectively, making it a leader in the field of natural language processing. However, on the evening of January 27, 2025, the Chinese technology giant Alibaba presented the Qwen 2.5-Max model, which, according to initial tests, may surpass DeepSeek and OpenAI in terms of analytical capabilities and contextual understanding. This model has been announced as the future of AI, ready for even more advanced tasks.
Founder – Liang Wenfeng
Liang Wenfeng is a distinguished mathematician and visionary who, before founding DeepSeek, managed a hedge fund, leveraging advanced AI algorithms in investment strategies. His unconventional problem-solving approach and deep technical expertise laid the foundation for DeepSeek’s success.Market reaction
The introduction of DeepSeek-R1 has triggered significant shifts in the global AI industry. Hardware companies, such as Nvidia, experienced a decline in market capitalization, highlighting the scale of this technology’s impact. There has also been immense interest on social media. In Poland alone, the X platform (formerly Twitter) recorded 10.8K posts about DeepSeek-V3.
