Open-source revolution: How DeepSeek-R1 challenges OpenAI’s o1 with superior processing, cost efficiency

The AI ​​industry is witnessing a seismic change with the introduction of Deepseek-R1, an open-source Open-Source reasoning model developed by the eponymous Chinese startup In depth. Released on January 20, this model questions the O1 of Openai – a flagship AI system – by offering performance comparable to a cost fraction. But how do these models accumulate in real world applications? And what does this mean for companies and developers?

In this article, we deeply dive into practical tests, practical implications and usable information to help technical decision -makers understand which model best meets their needs.

Real implications: why this comparison is important

Competition between Deepseek-R1 and OPENAI O1 is not only a reference question – this is a real impact. Companies are increasingly counting on AI for tasks such as data analysis, customer service automation, decision -making and coding assistance. The choice between these models can considerably affect profitability, optimization of workflow and innovation potential.

Key questions for businesses:

• Can Deepseek-R1 cost savings justify its adoption on Openai O1?
• How do these models work in real world scenarios such as mathematical calculation, reasoning-based analysis, financial modeling or software development?
• What are the compromises between open source flexibility (Deepseek-R1) and proprietary robustness (Openai O1)?

To answer these questions, we carried out practical tests through reasoning, solving mathematical problems, coding tasks and decision -making scenarios. Here is what we found.

Practical tests: how infeek and openai o1 perform

Question 1: Logical inference

If A = B, B = C and C ≠ D, what final conclusion can be drawn on A and D?

Analysis:

• OPENAI O1: reasoning well structured with formal declarations.
• Deepseek-R1: just as precise and more concise presentation.
• Treatment time: Deepseek (0.5s) compared to Openai (2S).
• Winner: Deepseek-R1 (equal precision, faster 4x, more concise).

Metric:

• Tokens: Deepseek (20) vs Openai (42).
• Cost: Deepseek ($ 0,00004) vs Openai ($ 0.0008).

Key insight: Deepseek-R1 obtains the same logical clarity with better efficiency, which makes it ideal for real-time applications at high volume.

Question 2: Define the problem of theory

In a room of 50 people, 30 like coffee, 25 like tea and 15 like both. How many people do neither coffee nor tea?

Analysis:

• OPENAI O1: Detailed mathematical notation.
• Deepseek-R1: Direct solution with clear steps.
• Treatment time: Deepseek (1S) against Openai (3S).
• Winner: Deepseek-R1 (clearer presentation, 3x faster).

Metric:

• Tokens: Deepseek (40) vs Openai (64).
• Cost: Deepseek ($ 0,00008) vs Openai ($ 0.0013).

Key insight: The concise approach to Deepseek-R1 maintains clarity while improving speed.

Question 3: Mathematical calculation

Calculate the exact value of: √ (144) + (15² ÷ 3) – 36.

Analysis:

• OPENAI O1: numbered steps with a detailed failure.
• Deepseek-R1: line calculation by clear line.
• Treatment time: Deepseek (1S) against Openai (2S).
• Winner: Deepseek-R1 (equal clarity, 2x faster).

Metric:

• Tokens: Deepseek (30) vs Openai (60).
• Cost: Deepseek ($ 0,00006) vs Openai ($ 0.0012).

Key insight: The two models are precise; Deepseek-R1 is more effective.

Question 4: Advanced mathematics

If x + y = 10 and x² + y² = 50, what are the precise values ​​of x and y?

Analysis:

• OPENAI O1: Complete solution with detailed steps.
• Deepseek-R1: effective solution with key steps highlighted.
• Treatment time: Deepseek (2S) against Openai (5s).
• Winner: Tie (Openai better for learning; Deepseek better for practice).

Metric:

• Tokens: Deepseek (60) vs Openai (134).
• Cost: Deepseek ($ 0,00012) vs Openai ($ 0.0027).

Key insight: The choice depends on the use case – Teaching in relation to the practical application. Deepseek-R1 excels in the speed and precision of logical and mathematical tasks, which makes it ideal for industries such as finance, engineering and data science.

Question 5: Investment analysis

A company has a budget of $ 100,000. Investment options: the option has given a yield of 7% with a risk of 20%, while option B gives a 5% yield with a risk of 10%. What option is maximizing the potential gain while minimizing the risk?

Analysis:

• OPENAI O1: Detailed analysis of risk-risk.
• Deepseek-R1: Direct comparison with key measurements.
• Treatment time: Deepseek (1.5s) against Openai (4S).
• Winner: Deepseek-R1 (sufficient analysis, 2.7x faster).

Metric:

• Tokens: Deepseek (50) vs Openai (110).
• Cost: Deepseek ($ 0,00010) vs Openai ($ 0.0022).

Key insight: The two models work well in decision-making tasks, but the concise and usable outputs of Deepseek-R1 make it more suitable for time-sensitive applications. Deepseek-R1 provides more effectively usable information.

Question 6: Calculation of efficiency

You have three delivery routes with different distances and time constraints:

• Route A: 120 km, 2 hours
• Route B: 90 km, 1.5 hours
• Route C: 150 km, 2.5 hours

What way is the most effective?

Analysis:

• OPENAI O1: Structured analysis with methodology.
• Deepseek-R1: clear calculations with a direct conclusion,
• Treatment time: Deepseek (1.5s) against Openai (3S).
• Winner: Deepseek-R1 (equal precision, 2x faster).

Metric:

• Tokens: Deepseek (50) vs Openai (112).
• Cost: Deepseek ($ 0,00010) vs Openai ($ 0.0022).

Key insight: The two are correct; Deepseek-R1 is more economical in time.

Question 7: Coding task

Write a function to find the most common element in a table with a temporal complexity o (N).

Analysis:

• OPENAI O1: Code well documented with explanations.
• Deepseek-R1: Clean the code with essential documentation.
• Treatment time: Deepseek (2S) against Openai (4S).
• Winner: depends on the use case (Deepseek for implementation, Openai for learning).

Metric:

• Tokens: Deepseek (70) vs Openai (174).
• Cost: Deepseek ($ 0,00014) vs Openai ($ 0.0035).

Key insight: The two are effective, with different forces for different needs. Deepseek-R1 coding and optimization skills are making it a solid competitor for software development and automation tasks.

Question 8: Algorithm design

Design an algorithm to check if a given number is a perfect palindrome without converting it to a chain.

Analysis:

• OPENAI O1: Complete solution with detailed explanation.
• Deepseek-R1: effective implementation with key points.
• Treatment time: Deepseek (2S) against Openai (5S).
• Winner: depends on the context (Deepseek for the implementation, Openai for understanding).

Metric:

• Tokens: Deepseek (70) vs Openai (220).
• Cost: Deepseek ($ 0,00014) vs Openai ($ 0.0044).

Key overview: The choice depends on the main need – Speed ​​against details.

Global performance metrics

• Total processing time: Deepseek (11.5S) vs Openai (28s).
• Total Tokens: Deepseek (390) against Openai (916).
• Total cost: Deepseek ($ 0.00078) against Openai ($ 0.0183).

Recommendations

1. Production environment
   • Primary: Deepseek-R1.
   • Advantages: faster treatment, cost reduction, sufficient precision.
   • Better for: API, high volume treatment, real -time applications.
2. Education / training
   • Primary: Openai O1.
   • Alternative: Deepseek-R1 for training exercises.
   • Best for: detailed explanations, learning new concepts.
3. Business development
   • Primary: Deepseek-R1 for implementation.
   • Secondary: OPENAI O1 for documentation.
   • Consider: hybrid approach based on specific needs.
4. Cost -sensitive operations
   • Strongly recommends: Deepseek-R1.
   • Reason: 2.4x faster, ~ 23x more profitable.
   • Note: Maintains quality while reducing the use of resources.

Conclusion: What model should you choose?

The choice between Deepseek-R1 and Openai O1 depends on your specific needs and priorities.

Choose Deepseek-R1 if:

• You prioritize profitability because it is 23 times more profitable.
• Faster treatment (2.4x faster on average) is crucial for your needs.
• You focus on real -time applications, high volume treatment or effective mathematical calculations.
• You are a startup, a researcher or a developer in search of an AI solution with an affordable open source.

Choose Openai O1 if:

• You need detailed reasoning and step -by -step explanations for educational or training purposes.
• General reasoning capacities and business reliability are essential for your projects.
• The budget is not a major constraint and you appreciate polished performance, complete documentation and business support.

Choose a hybrid approach if:

• You have various needs in different projects.
• You want to use Deepseek-R1 for rapid development and implementation.
• You need Openai O1 to create detailed documents or training documents.

Final reflections

The development of Deepseek-R1 means a transformer change in the development of AI, with a profitable and high performance alternative to commercial models like O1 of Openai. Its open source nature and robust reasoning capacities position it as a changing game for startups, developers and businesses concerned about the budget.

The analysis of the performance of Deepseek-R1 indicates a substantial increase in AI capabilities, offering not only cost savings, but also a measurably faster treatment (2.4x) and clearer outputs compared to the O1 of OpenAi. The combination of speed, efficiency and clarity by the model makes it an ideal choice for production environments and real -time applications.

As the AI ​​landscape is evolving, competition between Deepseek-R1 and OpenAi O1 is likely to stimulate innovation and improve accessibility, benefiting the entire ecosystem. Whether you are a technical decision -maker or a curious developer, now is the time to explore how these models can revolutionize your workflows and unlock new opportunities. The future of the AI ​​seems more and more nuanced, the models being assessed according to measurable performance rather than the affiliation of the brand.