I recently had an experiment as part of the company’s project – and I am excited (and a little frustration) to share its findings. While I was using Openai for a long time, I decided to test Deepseek (which is everywhere these days) to see if the low cost that is largely determined is really translated into great performance. What I found was a clear exchange between the cost and the cumin that every developer should take into account.
My experience: preparation and measurements
For this experience, I have prepared a simple text program that manages demanding the same basic logic. The inputs in the test were a fixed text of the analysis, then the text program implemented separate demands. I played this text program using three different configurations:
- Deepseek chat form on the Nebius platform:
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Recruitment response times: 6.95 seconds, 11.8 seconds and 12.44 seconds
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middle: About 10.4 seconds
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- Deepseek chat form on the original API:
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Recruitment response times: 20.1 seconds, 16.69 seconds, and 22.62 seconds
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middle: About 19.8 seconds
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- Openai GPT – 4O:
- Introduction response times: 4.62 seconds, 4.19 seconds, and 3.77 seconds
- middle: About 4.2 seconds
This timing was accurately recorded by writing down notes on a second screen while running the text program. The results clearly show that although GPT -4O is fast – the responses that last more than 4 seconds on average – the Deepseek responses are dramatically slower. Depending on the access method, Deepseek takes approximately 10 to 20 seconds per call.
Cost analysis: How cheaper Deepseek?
From the perspective of pricing, Dempsic is very attractive. The quoted prices are:
- Deepsek Origel API (Deepseek – Chat):
- Openai GPT – 4O:
- Input symbols: $ 2.50 per million symbols
- Output symbols: 10.00 dollars per million symbols
It reveals the comparison of the direct cost:
- For input symbols: 2.50/0.27≈9.26
- For directing symbols: 10.00/1.10≈9.09
Thus, Deepseek makes it almost 9 times cheaper From GPT – 4O for each of the distinctive icons of entry and output. This dramatic difference is particularly attractive to applications or projects of large size as budget restrictions are of utmost importance.
Additional considerations
Server resource restrictions
During the test, I discovered that the Deepseek platform is currently facing server capacity problems. Explain their official notice:
Due to the current server resource restrictions, we temporarily suspended the API service to prevent any potential effect on your operations.
This not only affects performance, but also indicates the limits of potential expansion of real world applications – especially those in which rapid response times are very important.
The suitability of tasks and use – the ponds of the era
In my experience, it became clear that if you run inactive or batch as the cumin is not a decisive factor, it may be the effectiveness of the cost in Deepseek (approximately 9 times) a big victory. However, for interactive applications- such as Chatbots or real time processing processing- where the user experience depends on rapid response times, the delay from 10 to 20 seconds of Deepseek may exceed the benefits of cost. Some experts suggest that parallel requests may help reduce these delays, but this adds another layer of complexity.
conclusion
The decision between Deepseek and GPT -4O is a clear exchange between cost and speed:
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Dibsic It provides an amazing cost feature – about 9 times cheaper per million symbols. This makes it an attractive option for the unrealistic time. However, my experience showed that its response times ranged from approximately 10 to 20 seconds, which could be an important defect for interactive applications.
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GPT – 4O It offers quick responses (about 4.2 seconds on average) thanks to its strong and developed infrastructure. For applications where speed is necessary, GPT -4O is the clear winner, albeit at a higher cost.
When I discovered directly, while the low price attractiveness is strong, the performance gap is a decisive factor. For developers and institutions, the choice must be guided by the specific needs of your application.
If the speed is of utmost importance, you may want to stick to the GPT -4O (or even explore emerging models such as Openai’s O3). But if your project can bear some delay and restrictions in the budget, it is a great concern, Deepseek provides a convincing alternative.
This experience gave me valuable visions in the current scene of Amnesty International – and I am excited to see how these differences develop as technology continues.
