The Gemini Pro model, which is similar in model size and class to GPT 3.5 Turbo, is generally similar in accuracy to GPT 3.5 Turbo, but somewhat inferior, and significantly inferior to GPT 4 on English tasks.
In particular, Gemini Pro performed slightly worse than GPT 3.5 Turbo on average, and was found to have issues such as response order bias in multiple-choice questions, mathematical inference using large numbers, and early termination of agent tasks. When using the default content filtering settings, there were also cases where aggressive content filtering resulted in response failures.
On the other hand, there were some advantages: Gemini Pro outperformed GPT 3.5 Turbo, especially on long and complex inference tasks.
Additionally, Gemini Pro outperforms GPT 3.5 Turbo and GPT-4 Turbo for languages where requests are not blocked (especially when generating text in other languages via translation), but there are a few languages for which Gemini Pro does not return an answer.
Mixtral, an open source model, is competitive with Gemini Pro and GPT 3.5 Turbo for knowledge-based QA and math tasks, but significantly underperforms on other tasks.
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