Gemini vs ChatGPT: Which is better? (8 months ago) Gemini Pro Vs. ChatGPT-3.5
**Language: **- The MMLU (Massive Multitask Language Understanding) benchmark test measures the capacity to interpret questions spanning 57 different subjects to evaluate general language understanding. In this test, Gemini Pro scored 79.13% compared to GPT-3.5’s 70%.
It’s interesting to note that this is the first model to do better on the test than human experts.
** Arithmetic Reasoning:** In the GSM8K benchmark test, which evaluates arithmetic reasoning and elementary school math problems, Gemini Pro scored an exceptionally high 86.5%, surpassing the score of GPT-3.5, which was 57.1%.
** Code Generation:**
Gemini Pro once again outperformed GPT-3.5 in the code generation test at the HumanEval benchmarks, scoring 67.7% as opposed to 48.1%.
The MATH benchmark assessment was the only one in which GPT-3.5 outperformed Gemini Pro, with GPT-3.5 scoring 34.1% to Gemini Pro’s marginally lower score of 32.6%.
Gemini Ultra Vs. ChatGPT-4
** General Capabilities**: In a 5-shot setting in the MMLU, Gemini Ultra scored an amazing 90.0%, surpassing GPT-4’s 86.4%.
Reasoning: A model’s ability to think in several steps is assessed on a variety of difficult tasks using the Big-Bench Hard benchmark test. In a comparable three-shot API configuration, Gemini Ultra scored 83.6%, almost exactly matching GPT-4’s 83.1%.
** Math: **Algebra and geometry were included in the more difficult math evaluation. In a 4-shot setup, Gemini Ultra was marginally ahead at 53.2% compared to 52.9% for GPT-4.
** Code Generation: **Gemini Ultra showed greater ability in Python code generation with scores of 74.4% and 74.9% (zero-shot settings) in the HumanEval and Natural2Code code generation benchmark tests, while GPT-4 scored 67% and 73.9%, respectively.
Image Processing (pixel only): Gemini Ultra outperformed GPT-4V with a 59.4% 0-shot, pass@1 score in the MMMU (multidisciplinary college-level reasoning) exam.
**** Video Processing: ****Gemini Ultra (pixel only) scored 53% in the MathVista, higher than GPT-4V’s 49.9%, for mathematical reasoning in visual contexts.
** Audio Processing: **Gemini Ultra significantly outperformed OpenAI’s Whisper v2 with a BLEU score of 40.1% in the CoVoST 2 benchmark test for automatic speech translation (21 languages).
In summary, both models perform admirably and hold their own in a variety of areas, according to this thorough analysis. Gemini’s multimodality shows a clear benefit when processing images, videos, and audio.
The two AI giants’ extraordinary powers are a testament to the field’s progress and a foundation for upcoming breakthroughs. In the end, these models will change how we interact with technology and the outside world as they continue to develop.
Conclusion
In conclusion, Gemini AI is a powerful tool that can be used for a variety of purposes. It can be used to generate creative text formats, like poems, code, scripts, musical pieces, emails, letters, etc. It can also be used to answer your questions in an informative way, even if they are open-ended, challenging, or strange. Gemini AI is still under development, but it has learned to perform many kinds of tasks, and it is constantly getting better. If you are looking for a versatile and powerful language model, Gemini AI is a great option.
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