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The AI industry is witnessing a seismic change with the introduction of Deepseek-R1, an open source reasoning model developed by the homonymous Chinese startup Veteran. Run on January 20, this model is challenging OPENAI O1, an insignia system, offering a 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 immerse ourselves deeply in practical tests, practical implications and processable ideas to help technical decision makers to understand which model adapts better to their needs.
Real world implications: why this comparison is important
The competition between Depseek-R1 and Opadai O1 is not just about reference points, it is an impact on the real world. Companies are increasingly depending on AI for tasks such as data analysis, customer service automation, decision making and coding assistance. The choice between these models can significantly affect profitability, the optimization of the workflow and the innovation potential.
Key questions for companies:
- Can the Deepseek-R1 cost savings justify your adoption on Openai O1?
- How do these models work in real world scenarios such as mathematical calculation, analysis based on reasoning, financial modeling or software development?
- What are the compensation between open source flexibility (Deepseek-R1) and patented robustness (Openai O1)?
To answer these questions, we perform practical tests through reasoning, the mathematical resolution of problems, coding tasks and decision -making scenarios. This is what we find.
Practical tests: how Deepseek and OpenAi work O1
Question 1: Logic inference
If A = B, B = C and C ≠ D, what definitive conclusion can be extracted on A and D?
Analysis:
- OpenAI O1: well -structured reasoning with formal statements.
- Deepseek-R1: Equally accurate and more concise presentation.
- Processing time: Deepseek (0.5) versus OpenAi (2s).
- Winner: Deepseek-R1 (equal precision, 4x faster, more concise).
Metrics:
- Tokens: Deepseek (20) vs OpenAi (42).
- Cost: Deepseek ($ 0.00004) vs OpenAi ($ 0.0008).
Key insight: Deepseek-R1 achieves the same logical clarity with better efficiency, which makes it ideal for high volume applications in real time.
Question 2: Set theory problem
In a room of 50 people, at 30 as coffee, 25 as tea and 15 as 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) versus OpenAi (3s).
- Winner: Deepseek-R1 (clearer presentation, 3x faster).
Metrics:
- Tokens: Deepseek (40) vs OpenAi (64).
- Cost: Deepseek ($ 0.00008) vs OpenAi ($ 0.0013).
Key insight: The concise approach of 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 breakdown.
- Deepseek-R1: Clear line calculation.
- Processing time: Deepseek (1s) versus OpenAi (2s).
- Winner: Deepseek-R1 (equal clarity, 2 times faster).
Metrics:
- Tokens: Deepseek (30) vs OpenAi (60).
- Cost: Deepseek ($ 0.00006) vs OpenAi ($ 0.0012).
Key insight: Both models are precise; Deepseek-R1 is more efficient.
Question 4: Advanced Mathematics
If x + y = 10 and x² + y² = 50, what are Xey’s precise values?
Analysis:
- OpenAI O1: Integral solution with detailed steps.
- DEPEEEK-R1: Efficient solution with highly highlighted steps.
- PROCESSING TIME: DEPEEEK (2S) versus OpenAI (5S).
- Winner: Tie (OpenAi better to learn; Deepseek better for practice).
Metrics:
- Tokens: Deepseek (60) vs OpenAi (134).
- Cost: Deepseek ($ 0.00012) vs OpenAi ($ 0.0027).
Key insight: The choice depends on the case of use: teaching versus practical application. Deepseek-R1 stands out in speed and precision for logical and mathematical tasks, so it is ideal for industries such as finance, engineering and data science.
Question 5: Investment analysis
A company has a $ 100,000 budget. Investment options: option A produces a 7% yield at a risk of 20%, while option B produces a 5% yield with a 10% risk. What option maximizes potential gain and minimizes risk?
Analysis:
- OPENAI O1: Detailed Risk-Reore analysis.
- Deepseek-R1: Direct comparison with key metrics.
- Processing time: Deepseek (1.5s) versus OpenAi (4S).
- Winner: Deepseek-R1 (sufficient analysis, 2.7x faster).
Metrics:
- Tokens: Deepseek (50) vs OpenAi (110).
- Cost: Deepseek ($ 0.00010) vs OpenAi ($ 0.0022).
Key insight: Both models work well in decision-making tasks, but the concise and processable outputs of Deepseek-R1 make it more suitable for time sensitive applications. DEPEEEK-R1 Provides more efficient processable ideas.
Question 6: Efficiency calculation
It has three delivery routes with different distances and time limitations:
- Route A: 120 km, 2 hours
- Route B: 90 km, 1.5 hours
- Route C: 150 km, 2.5 hours
What route is more efficient?
Analysis:
- OpenAI O1: Structured analysis with methodology.
- Deepseek-R1: Clear calculations with direct conclusion,
- Processing time: Deepseek (1.5s) versus OpenAi (3s).
- Winner: Deepseek-R1 (equal precision, 2 times faster).
Metrics:
- Tokens: Deepseek (50) vs OpenAi (112).
- Cost: Deepseek ($ 0.00010) vs OpenAi ($ 0.0022).
Key insight: Both are precise; Deepseek-R1 is more efficient over time.
Question 7: Coding task
Write a function to find the most frequent element in a matrix with O (n) complexity of time.
Analysis:
- OpenAI O1: well documented code with explanations.
- Deepseek-R1: Clean code with essential documentation.
- Processing time: Deepseek (2s) versus OpenAi (4s).
- Winner: It depends on the case of use (Deepseek for implementation, OpenAi for learning).
Metrics:
- Tokens: Deepseek (70) vs OpenAi (174).
- Cost: Deepseek ($ 0.00014) vs OpenAi ($ 0.0035).
Key insight: Both are effective, with different strengths for different needs. The Deepseek-R1 coding and optimization competence makes it a strong contender for software development and automation tasks.
Question 8: Algorithm Design
Design an algorithm to verify if a given number is a perfect palindromo without turning it into a chain.
Analysis:
- OpenAI O1: Integral solution with a detailed explanation.
- Deepseek-R1: efficient implementation with key points.
- PROCESSING TIME: DEPEEEK (2S) versus OpenAI (5S).
- Winner: It depends on the context (Deepseek for the implementation, OpenAi for understanding).
Metrics:
- Tokens: Deepseek (70) vs OpenAi (220).
- Cost: Deepseek ($ 0.00014) vs OpenAi ($ 0.0044).
Key information: The choice depends on the primary need: speed versus details.
General performance metrics
- Total processing time: Deepseek (11.5s) vs OpenAi (28s).
- Total Total: Deepseek (390) versus OpenAi (916).
- Total cost: Deepseek ($ 0.00078) versus OpenAi ($ 0.0183).
Recommendations
- Production environment
- Primary: Deepseek-R1.
- Benefits: faster processing, lower costs, sufficient precision.
- The best for: API, high volume processing, real -time applications.
- Educational/Training
- Primary: OpenAi O1.
- Alternative: Deepseek-R1 for practice exercises.
- The best for: detailed explanations, learning new concepts.
- Business development
- Primary: Deepseek-R1 for implementation.
- Secondary: OpenAI O1 for documentation.
- Consider: hybrid approach based on specific needs.
- Cost -sensitive operations
- I firmly recommend: 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 Depseek-R1 and OpenAi O1 depends on their specific needs and priorities.
Choose Deepseek-R1 yes:
- Prioritize profitability efficiency, since it is 23 times more profitable.
- Faster processing (2.4x faster on average) is crucial for your needs.
- Your approach is in real -time applications, high volume processing or efficient mathematical calculations.
- You are a startup, researcher or developer looking for a solution of affordable, open and customizable source.
OPENAI O1 yes:
- You need detailed reasoning and explanations step by step for educational or training purposes.
- The wide reasoning capabilities and business degree reliability are critical for their projects.
- The budget is not an important restriction, and you value polishing performance, integral documentation and corporate support.
Choose a hybrid approach if:
- You have different needs in different projects.
- You want to use Deepseek-R1 for rapid development and implementation.
- You need OPENAI O1 to create detailed documentation or training materials.
Final thoughts
The increase in Deepseek-R1 means a transformative change in the development of AI, presenting a high-performance profitable alternative to commercial models such as OpenAi’s O1. Its open source nature and its robust reasoning capabilities position it as a change of play for new companies, developers and companies aware of the budget.
The Deepseek-R1 performance analysis indicates a substantial advance in AI capacities, which offers not only cost savings but also a meditable processing (2.4x) and clearer outputs compared to OPENAI O1. The combination of speed, efficiency and clarity of the model makes it an ideal option for production environments and applications in real time.
As the panorama of the evolves, it is likely that the competition between Depseek-R1 and OpenAi O1 stimulates innovation and improve accessibility, benefiting the entire ecosystem. Whether it is a technical decision maker or an inquisitive developer, now it is time to explore how these models can revolutionize their workflows and unlock new opportunities. The future of AI seems increasingly nuanced, and the models are evaluated depending on measurable performance instead of the brand affiliation.
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