Open Source Revolution: How Deepseek-R1 Openais O1 with superior processing, challenges cost efficiency

The AI industry pursues a seismic shift with the introduction of Deepseek-R1A modern open source argumentation model developed by the Chinese startup of the same name Deepseek. This model published on January 20 is challenging Openai’s O1 – A flagship -KI system – by delivering a comparable performance to a fraction of the costs. But how do these models stack into real applications? And what does that mean for companies and developers?

In this article, we immerse yourself in practical tests, practical effects and implementable knowledge to help technical decision -makers understand which model best suits your needs.

Implications of the real world: Why this comparison is important

The competition between Deepseek-R1 and Openai O1 is not just about benchmarks-es about real effects. Companies are increasingly relying on AI for tasks such as data analysis, customer towering, decision -making and coding aid. The choice between these models can significantly influence cost efficiency, workflow optimization and innovation potential.

Key questions for companies:

• Can Deepseek-R1’s Cost savings justify its introduction to Openaai O1?
• How are these models completed in real scenarios such as mathematical calculation, argumentative analysis, financial modeling or software development?
• What are the compromises between open source flexibility (deepseek-r1) and proprietary robustness (Openaai O1)?

In order to answer these questions, we carried out practical tests with regard to argumentation, mathematical problem solving, coding tasks and decision scenarios. We found the following.

Practical tests: how Deepseek and Openaai O1 cut off

Question 1: Logical inference

If a = b, b = c and c ≠ d, what final conclusion can be drawn to A and D?

Analysis:

• Openai O1: Well -structured thinking with formal statements.
• Deepseek-R1: Same exact, more concise presentation.
• Processing time: Deepseek (0.5s) against Openai (2S).
• Winner: Deepseek-R1 (same accuracy, 4x faster, more concise).

Metrics:

• Token: Deepseek (20) against Openai (42).
• Costs: Deepseek ($ 0.00004) against Openai (USD 0.0008).

Key inspection: Deepseek-R1 achieves the same logical clarity with better efficiency and makes it ideal for real-time applications with a high volume.

Question 2: Set the problem of theory

In a room with 50 people, 30 like coffee, 25 like tea and 15 like both. How many people do not like coffee or tea?

Analysis:

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

Metrics:

• Token: Deepseek (40) against Openai (64).
• Costs: Deepseek ($ 0.00008) against Openai ($ 0.0013).

Key inspection: The precise approach of Deepseek-R1 maintains clarity and improves the speed.

Question 3: Mathematical calculation

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

Analysis:

• Openai O1: Numbered steps with detailed breakdown.
• Deepseek-R1: Clear-by-line calculation.
• Processing time: Deepseek (1S) against Openai (2S).
• Winner: Deepseek-R1 (same clarity, 2x faster).

Metrics:

• Token: Deepseek (30) against Openai (60).
• Cost: Deepseek ($ 0.00006) against Openai ($ 0.0012).

Key inspection: Both models are exactly; Deepseek-R1 is more efficient.

Question 4: Extended mathematics

If X + Y = 10 and X² + Y² = 50, what are the exact values of X and Y?

Analysis:

• Openai O1: Comprehensive solution with detailed steps.
• Deepseek-R1: Efficient solution with the most important steps.
• Processing time: Deepseek (2S) against Openai (5S).
• Winner: tie (Openai better for learning; Deepseek better for practicing).

Metrics:

• Token: Deepseek (60) against Openai (134).
• Cost: Deepseek ($ 0.00012) against Openai ($ 0.0027).

Key inspection: The selection depends on the application – lessons of practical application. Deepseek-R1 is characterized in speed and accuracy for logical and mathematical tasks, which makes it ideal for industries such as finance, engineering and data sciences.

Question 5: Investment analysis

A company has a budget of $ 100,000. Annex options: Option A results in a return of 7% with a risk of 20%, while option B results in a return of 5% with a risk of 10%. Which option maximizes the potential profit and minimizes the risk?

Analysis:

• Openaai O1: Detailed analysis of the risk return.
• Deepseek-R1: Direct comparison with important metrics.
• Processing time: Deepseek (1.5S) against Openai (4S).
• Winner: Deepseek-R1 (sufficient analysis, 2.7x faster).

Metrics:

• Token: Deepseek (50) against Openai (110).
• Costs: Deepseek ($ 0.00010) against Openai ($ 0.0022).

Key inspection: Both models are well coordinated in decision-making tasks, but the concise and implementable editions of Deepseek-R1 make it more suitable for time-sensitive applications. Deepseek-R1 offers implementable insights more efficient.

Question 6: Efficiency calculation

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

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

Which route is most efficient?

Analysis:

• Openai O1: Structured analysis with methodology.
• Deepseek-R1: Clear calculations with direct conclusion,
• Processing time: Deepseek (1.5S) against Openai (3S).
• Winner: Deepseek-R1 (same accuracy, 2x faster).

Metrics:

• Token: Deepseek (50) against Openai (112).
• Costs: Deepseek ($ 0.00010) against Openai ($ 0.0022).

Key inspection: Both are exactly; Deepseek-R1 is stronger in time.

Question 7: Coding task

Write a function to find the most common element in an array with O (s) time complexity.

Analysis:

• Openai O1: Well -documented code with explanations.
• Deepseek-R1: Clean code with essential documentation.
• Processing time: Deepseek (2S) against Openai (4S).
• Winner: depends on the application (Deepseek for implementation, Openai for learning).

Metrics:

• Token: Deepseek (70) against Openai (174).
• Costs: Deepseek ($ 0.00014) against Openai ($ 0.0035).

Key inspection: Both are effective, with different strengths for different needs. The coding skills and optimization functions of Deepseek-R1 make it a strong contender on software development and automation tasks.

Question 8: Algorithm Design

Design an algorithm to check whether a certain number is a perfect palindrome without converting it into a string.

Analysis:

• Openai O1: Comprehensive solution with a detailed explanation.
• Deepseek-R1: Efficient implementation with important points.
• Processing time: Deepseek (2S) against Openai (5S).
• Winner: depends on the context (Deepseek for implementation, Openai for understanding).

Metrics:

• Token: Deepseek (70) against Openai (220).
• Cost: Deepseek ($ 0.00014) against Openai ($ 0.0044).

Key Insight: The selection depends on the primary need – speed compared to details.

Total performance indicators

• Total processing time: Deepseek (11.5s) against Openai (28S).
• Total tokens: Deepseek (390) against Openai (916).
• Total costs: Deepseek ($ 0.00078) compared to Openai (USD 0.0183).

Recommendations

1. Production environment
   • Primary: deepseek-r1.
   • Advantages: faster processing, lower costs, sufficient accuracy.
   • Best for: APIs, processing with a high volume, real -time applications.
2. Education/training
   • Primary: Openai O1.
   • Alternative: Deepseek-R1 for exercises.
   • Best for: detailed explanations, learn new concepts.
3. Corporate development
   • Primarily: Deepseek-R1 for implementation.
   • Secondary: Openai O1 for documentation.
   • Remember: hybrid approach based on certain needs.
4. Cost sensitive operations
   • Recommend: Deepseek-R1.
   • Reason: 2.4x faster, ~ 23x more cost -efficient.
   • Note: Stop the quality and at the same time reduce the use of the resources.

Conclusion: Which model should you choose?

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

Choose Deepseek-R1 if:

• They prioritize cost efficiency because they are 23x cheaper.
• Faster processing (2.4x faster on average) is of crucial importance for your needs.
• Your focus is on real -time applications, high -volume processing or efficient mathematical calculations.
• You are a startup, researcher or developer who is looking for an affordable open source AI solution.

Choose Openaai O1 if:

• You need detailed argument and step-by-step declarations for educational or training purposes.
• Wide argumentation functions and reliability of corporate quality are of crucial importance for their projects.
• The budget is not a major restriction, and it appreciates polished performance, comprehensive documentation and company support.

Choose a hybrid approach if:

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

Last thoughts

The rise of Deepseek-R1 means a transformative shift in AI development and offers an inexpensive, powerful alternative to commercial models such as Openas O1. His open source nature and robust argumentation skills position it as a game channel for startups, developers and budget-conscious companies.

The performance analysis of Deepseek-R1 indicates a considerable progress of the AI functions, which not only provides cost savings, but also measurably faster processing (2.4x) and clearer expenses compared to OpenAS O1. The combination of speed, efficiency and clarity of the model makes it an ideal choice for production environments and real -time applications.

While the AI landscape is developing, the competition between Deepseek-R1 and Openai O1 will probably flare up the innovation and improve accessibility, which benefits the entire ecosystem. Regardless of whether you are a technical decision -makers or a curious developer, the moment is to examine how these models can revolutionize your workflows and unlock new opportunities. The future of the AI appears increasingly nuanced, whereby the models are rated on a measurable performance rather than on brand affiliation.