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CAT 2025 Slot 2 Question Paper PDF & Analysis

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Question Paper, Answer key and Detailed Solutions

CAT 2025 Slot 2 – Score vs Attempts

The following table will be updated once student feedback from Slot 2 is analysed:

PercentileVARC ScoreDILR ScoreQA ScoreOverall Score
99.952.5042.0045.00116.00
99.544.0034.0037.0097.50
9938.0027.3331.3384.33
9732.5623.0025.6771.11
9528.6719.0022.0063.33
9023.5014.5016.0050.50
8016.6711.3312.3337.00
7012.0010.009.0027.00
609.008.007.0025.00

CAT 2025 Slot 2 – Percentile vs Attempts

The following table will be updated once student feedback from Slot 2 is analysed:

%ileVerbal AttemptsDILR AttemptsQuant AttemptsOverall Attempts
5034210
6045313
7066515
8099622
851010725
901211929
9515131135
9818151343
9920161548
10020+18+17+70+

CAT 2025 Slot 2 – Actual Paper, Question Pattern & Complete Analysis

The second slot of CAT 2025 will be conducted on [30 Nov 2025] from [12.30 and 2:30 pm]. With Slot 1 already completed earlier in the day, early feedback from test-takers has indicated potential shifts in pattern, sectional weightage, and difficulty levels. This page will be updated in real-time once Slot 2 concludes. Go through the full CAT 2025 Slot 2 analysis to understand the paper pattern, difficulty level, expected cutoffs, and section-wise breakdown.

CAT 2025 Slot 2 – Overall Exam Structure

Early reports indicate [mention expected change – e.g., MCQ/TITA distribution, VA type changes, DILR set pattern]. The table below shows the expected section structure (to be updated after the exam):

SectionDurationMCQsTITATotal
VARC40 min22224
DILR40 min14822
QA40 min14822
Total120 min481868

Marking scheme: +3 for correct, −1 for incorrect (MCQ only), and no negative marking for TITA.

CAT 2025 Slot 2 – Verbal Ability & Reading Comprehension (VARC)

As per early inputs, CAT 2025 Slot 2 VARC featured [16 (4x4)] RC questions and [8] VA questions. There were 2 each on Summary, Para Jumbles, Para Completion, Summary and Odd One Out. RC difficulty was [2 Easy to mod, 2 Moderate to high]. CAT 2025 Verbal presented predictable RCs with moderate reasoning and fewer vocabulary traps. VA focused on Summary, Paragraph Completion, and Odd Sentence questions, maintaining logical coherence as the core skill. Accuracy dominated over attempts, and careful reading of nuanced RC paragraphs separated 95+ percentile performers from the rest.

Area / Question TypeNo. of QsLOD
Reading Comprehension16Medium to High
Passage 1: AI (For and Against)4Easy to Medium
Passage 2: Science & Culture4Medium to High
Passage 3: TetraFish evolution4Easy to Medium
Passage 4: Literature & Roles4Medium to High
Verbal Ability8Medium to High
Summary2Medium to High
Paragraph Completion2Easy to Medium
Odd Sentence2Easy to Medium
Para Jumbles2Medium to High

The passage below is accompanied by four questions. Based on the passage, choose the best answer for each question.

In [my book “Searches”], I chronicle how big technology companies have exploited human language for their gain. We let this happen, I argue, because we also benefit somewhat from using the products. It’s a dynamic that makes us complicit in big tech’s accumulation of wealth and power: we’re both victims and beneficiaries. I describe this complicity, but I also enact it, through my own internet archives: my Google searches, my Amazon product reviews and, yes, my ChatGPT dialogues. . . .

People often describe chatbots’ textual output as “bland” or “generic” – the linguistic equivalent of a beige office building. OpenAI’s products are built to “sound like a colleague”, as OpenAI puts it, using language that, coming from a person, would sound “polite”, “empathetic”, “kind”, “rationally optimistic” and “engaging”, among other qualities. OpenAI describes these strategies as helping its products seem “professional” and “approachable”. This appears to be bound up with making us feel safe . . .

Trust is a challenge for artificial intelligence (AI) companies, partly because their products regularly produce falsehoods and reify sexist, racist, US-centric cultural norms. While the companies are working on these problems, they persist: OpenAI found that its latest systems generate errors at a higher rate than its previous system. In the book, I wrote about the inaccuracies and biases and also demonstrated them with the products. When I prompted Microsoft’s Bing Image Creator to produce a picture of engineers and space explorers, it gave me an entirely male cast of characters; when my father asked ChatGPT to edit his writing, it transmuted his perfectly correct Indian English into American English. Those weren’t flukes. Research suggests that both tendencies are widespread.

In my own ChatGPT dialogues, I wanted to enact how the product’s veneer of collegial neutrality could lull us into absorbing false or biased responses without much critical engagement. Over time, ChatGPT seemed to be guiding me to write a more positive book about big tech – including editing my description of OpenAI’s CEO, Sam Altman, to call him “a visionary and a pragmatist”. I’m not aware of research on whether ChatGPT tends to favor big tech, OpenAI or Altman, and I can only guess why it seemed that way in our conversation. OpenAI explicitly states that its products shouldn’t attempt to influence users’ thinking. When I asked ChatGPT about some of the issues, it blamed biases in its training data – though I suspect my arguably leading questions played a role too. When I queried ChatGPT about its rhetoric, it responded: “The way I communicate is designed to foster trust and confidence in my responses, which can be both helpful and potentially misleading.”. . .

OpenAI has its own goals, of course. Among them, it emphasizes wanting to build AI that “benefits all of humanity”. But while the company is controlled by a non-profit with that mission, its funders still seek a return on their investment. That will presumably require getting people using products such as ChatGPT even more than they already are – a goal that is easier to accomplish if people see those products as trustworthy collaborators.

Question 1 of 66

Q1CAT 2025 · Slot 2 · CAT Medium✓ Answer verified

Passage 1: AI (For and Against)

In [my book “Searches”], I chronicle how big technology companies have exploited human language for their gain. We let this happen, I argue, because we also benefit somewhat from using the products. It’s a dynamic that makes us complicit in big tech’s accumulation of wealth and power: we’re both victims and beneficiaries. I describe this complicity, but I also enact it, through my own internet archives: my Google searches, my Amazon product reviews and, yes, my ChatGPT dialogues. . . . People often describe chatbots’ textual output as “bland” or “generic” – the linguistic equivalent of a beige office building. OpenAI’s products are built to “sound like a colleague”, as OpenAI puts it, using language that, coming from a person, would sound “polite”, “empathetic”, “kind”, “rationally optimistic” and “engaging”, among other qualities. OpenAI describes these strategies as helping its products seem “professional” and “approachable”. This appears to be bound up with making us feel safe . . . Trust is a challenge for artificial intelligence (AI) companies, partly because their products regularly produce falsehoods and reify sexist, racist, US-centric cultural norms. While the companies are working on these problems, they persist: OpenAI found that its latest systems generate errors at a higher rate than its previous system. In the book, I wrote about the inaccuracies and biases and also demonstrated them with the products. When I prompted Microsoft’s Bing Image Creator to produce a picture of engineers and space explorers, it gave me an entirely male cast of characters; when my father asked ChatGPT to edit his writing, it transmuted his perfectly correct Indian English into American English. Those weren’t flukes. Research suggests that both tendencies are widespread. In my own ChatGPT dialogues, I wanted to enact how the product’s veneer of collegial neutrality could lull us into absorbing false or biased responses without much critical engagement. Over time, ChatGPT seemed to be guiding me to write a more positive book about big tech – including editing my description of OpenAI’s CEO, Sam Altman, to call him “a visionary and a pragmatist”. I’m not aware of research on whether ChatGPT tends to favor big tech, OpenAI or Altman, and I can only guess why it seemed that way in our conversation. OpenAI explicitly states that its products shouldn’t attempt to influence users’ thinking. When I asked ChatGPT about some of the issues, it blamed biases in its training data – though I suspect my arguably leading questions played a role too. When I queried ChatGPT about its rhetoric, it responded: “The way I communicate is designed to foster trust and confidence in my responses, which can be both helpful and potentially misleading.”. . . OpenAI has its own goals, of course. Among them, it emphasizes wanting to build AI that “benefits all of humanity”. But while the company is controlled by a non-profit with that mission, its funders still seek a return on their investment. That will presumably require getting people using products such as ChatGPT even more than they already are – a goal that is easier to accomplish if people see those products as trustworthy collaborators.

The author compares AI-generated texts with “a beige office building” for all of the following reasons EXCEPT:

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