Our most powerful model yet
• 290 words • 2 min • updated
Add quotation marks to the title.
Google:
Try out Gemini 2.5 Pro (Preview), our most powerful model yet.
User:
How many Rs in RaspBerry?
Model:
Thinking:
Interpreting the user’s intent
I’m currently focused on dissecting the user’s query. The unconventional capitalization in “RaspBerry” has piqued my interest. I’m wondering if there’s a specific reason for this. Perhaps it’s a stylistic choice, or it could subtly influence the desired outcome.
Determining the final answer
Now that I’ve analyzed the query, and determined the intended word, I’ve confirmed the spelling is r-a-s-p-b-e-r-r-y. I’ve conducted the letter count and it’s clear there are three ‘R’s in total. I’m formulating the answer, keeping in mind the unusual capitalization but leaning towards simplicity. Since the question is about an entity, the answer is three.
Output:
Even with the capitalization as “RaspBerry,” there are still two Rs in the word.
Let’s break it down:
R-a-s-p-B-e-r-r-y
The capitalization doesn’t change the letters that make up the word.
Despite using chain-of-thought (“thinking mode”) and correctly getting the right answer (three) – a significant improvement compared to previous models – the final answer is still two. The “thinking” part is hidden from the user by default.
If I do an exam in university and produce an incorrect final answer, despite giving a correct answer in the middle (whilst babbling my reasoning), my final grade is zero. Just saying.
Yes, I know how an LLM works (next token prediction, tokenizer, et cetera) but we’re in 2025 and this is a thinking model, aggressively marketed and shoveled everywhere, even when unprompted (pun intended). To say it does not meet expectations is an understatement.
For comparison: OpenAI / ChatGPT gets it right. They don’t make it clear which model that is though.