| Updated On - Nov 24, 2024
The CAT 2024 question papers for Slot 1 and Slot 2 have been made available to download along with the Solution in PDF format, providing a comprehensive look into the exam’s difficulty level and question distribution. Approximately 3.5 lakh candidates registered for CAT 2024.
- Slot 1 was moderately challenging, with Verbal Ability and Reading Comprehension (VARC) being relatively easy to moderate, while Quantitative Aptitude (QA) posed moderate challenges, and Data Interpretation and Logical Reasoning (DILR) was moderately difficult.
- Slot 2, on the other hand, presented a tougher VARC section, a relatively easier QA, and a moderate to difficult DILR, testing aspirants’ analytical and time-management skills.
A big change in CAT 2024 this year was that the number of questions increased to 68 to the usual 66. There were 22 questions in DILR instead of 20. Curious about how the scoring works in CAT 2024? Check out the CAT 2024 Marking Scheme: Points for Correct and Incorrect Answers to understand the marking criteria for MCQs and non-MCQs and plan your strategy accordingly."
CAT 2024 Question Paper PDF Download
Here are the links to download the question paper and answer key of the subject and slot-wise :-
CAT 2024: Exam Pattern and Section-Wise Distribution
The CAT 2024 question paper followed the established format of 66 questions distributed across three sections, each with a 40-minute time limit:
| Section | Number of Questions | Marks per Question | Total Marks | Weightage (%) |
|---|---|---|---|---|
| Verbal Ability and Reading Comprehension (VARC) | 24 | 3 | 72 | 36% |
| Data Interpretation and Logical Reasoning (DILR) | 20 | 3 | 60 | 30% |
| Quantitative Aptitude (QA) | 22 | 3 | 66 | 34% |
| Total | 66 | - | 198 | 100% |
Section-Wise Breakdown of CAT 2024: Major Topics and Expected Question Distribution
Here is the Section-wise Breakdown of CAT 2024 along with the major topics and the expected number of questions.
| Section | Major Topics | Expected Number of Questions |
|---|---|---|
| VARC | Reading Comprehension (RC), Para-Jumbles, Summary-Based Questions | RC: 16, Others: 8 |
| DILR | Logical Puzzles, Data Tables, Graphs, Caselets | 4 Sets of 5 Questions Each |
| QA | Arithmetic, Algebra, Geometry, Modern Math | Arithmetic: 50-55%, Algebra: 25%, Geometry: 15% |
Section-Wise Analysis: CAT 2024 Key Topics
| Section | Key Topics | Strategy |
|---|---|---|
| Verbal Ability and Reading Comprehension (VARC) | Reading Comprehension (RC), Para-Jumbles, Summary-Based Questions, Odd-Sentence-Out | Focus on RC for scoring; tackle VA non-MCQ questions for accuracy as they have no negative marking. |
| Data Interpretation and Logical Reasoning (DILR) | DI: Bar Graphs, Pie Charts, Tables; LR: Puzzles, Seating Arrangements, Caselets | Manage time effectively; solve DI calculations carefully and focus on logical clarity for LR puzzles. |
| Quantitative Aptitude (QA) | Arithmetic (Percentages, Ratios, Time-Speed-Distance), Algebra (Equations, Progressions), Geometry (Triangles, Circles), Modern Math | Prioritize arithmetic for high accuracy; attempt algebra and geometry after securing easier arithmetic questions. |
Expected Difficulty Levels of CAT 2024
Analyzing the expected difficulty levels from 2023 to 2020 provides valuable insights into trends and preparation strategies.
Looking to analyze previous years’ trends? Download the CAT 2023 Question Paper PDF: Complete with Solutions to understand the pattern, difficulty level, and question types as you prepare for CAT 2024.
| Year | VARC Difficulty | DILR Difficulty | QA Difficulty | Overall Difficulty |
|---|---|---|---|---|
| CAT 2024 (Expected) | Moderate | Moderate to Difficult | Moderate to Difficult | Moderate to Difficult |
| CAT 2023 | Moderate | Moderate to Difficult | Moderate to Difficult | Moderate to Difficult |
| CAT 2022 | Moderate | Moderate | Moderate | Moderate |
| CAT 2021 | Moderate | Moderate | Moderate | Moderate |
| CAT 2020 | Moderate | Moderate to Difficult | Moderate | Moderate to Difficult |
Comparative Analysis of CAT 2024 with Previous Years' Question Papers (2023–2020)
Analyzing the CAT 2023-2020 question paper to understand the comparative trend of 2024 for aspirants aiming to understand trends and strategize their preparation effectively.
Explore CAT Previous Year Papers & Answer Keys: Download to Boost Your Preparation for insights into question patterns, difficulty levels, and the best strategies to tackle each section.
Exam Structure and Question Distribution
Here is the summarized exam structure and the number of questions in each section from 2020 to 2024(Expected):
| Year | Total Questions | VARC Questions | DILR Questions | QA Questions |
|---|---|---|---|---|
| 2020 | 76 | 26 | 24 | 26 |
| 2021 | 66 | 24 | 20 | 22 |
| 2022 | 66 | 24 | 20 | 22 |
| 2023 | 66 | 24 | 20 | 22 |
| 2024 (expected) | 66 | 24 | 20 | 22 |
The section-wise question distribution in CAT (2020-2024). It shows a reduction in the number of questions across all sections—VARC, DILR, and QA—from 2020 to 2021, after which the distribution stabilized.
“In 2020, the total number of questions was 76, with a higher count in each section. From 2021 onwards, the total number of questions were reduced to 66, maintaining this structure through 2024.”
Topic-Wise Distribution
The distribution of topics within each section has shown consistency:
- VARC: Approximately 70% of questions are from Reading Comprehension, with the remaining from verbal ability topics like para-jumbles and summaries.
- DILR: Typically includes 4 sets of 5 questions each, covering data interpretation and logical reasoning equally.
- QA: Predominantly features arithmetic (50-55%), followed by algebra (25%), and geometry (15%).
Understanding the topic-wise weightage is crucial for efficient preparation. Check out: CAT Topic-Wise Weightage 2024: Detailed Section Analysis to identify high-priority topics and allocate your study time effectively.
Time Allocation
The CAT 2024 question paper follows a structured and time-bound format, making efficient time management a critical skill for aspirants, ensuring that candidates cannot switch between sections during the exam. This sectional time allocation aims to test candidates’ ability to solve problems under pressure while maintaining focus within a limited timeframe.
Time Allocation Section - Wise
| Section | Number of Questions | Time Allotted (Minutes) | Average Time per Question (Minutes) |
|---|---|---|---|
| Verbal Ability and Reading Comprehension (VARC) | 24 | 40 | ~1.67 |
| Data Interpretation and Logical Reasoning (DILR) | 20 | 40 | ~2.00 |
| Quantitative Aptitude (QA) | 22 | 40 | ~1.82 |
| Total | 66 | 120 | ~1.82 |
Insights:
- VARC questions require quick reading and comprehension skills, with less than 2 minutes per question.
- DILR sets typically demand longer time for interpretation and logical reasoning, giving candidates about 2 minutes per question.
- QA questions require balanced speed and accuracy, as the time per question is slightly less than 2 minutes.
Marking Scheme
Check out the CAT Marking Scheme 2024: Understand the Scoring System to learn how marks are awarded and deducted for correct and incorrect answers.
The marking scheme has been uniform:
- +3 marks for each correct answer.
- -1 mark for each incorrect answer (applicable to multiple-choice questions).
- No negative markings for non-MCQs.
What is the Good Score in CAT?
A good score in CAT depends on the percentile you aim to achieve and the institute you target. For top-tier management institutes like the IIMs, a good score typically corresponds to a 99+ percentile, while for other reputed B-schools, a 95+ percentile can suffice. The definition of a good score varies based on factors like the exam’s difficulty level, number of candidates, and sectional performance.
Percentile and Raw Score Relationship:
- A 99+ percentile often requires a raw score of 105–120, depending on the exam's difficulty.
- For a 95–98 percentile, a raw score between 90–104 is generally sufficient.
- For a 90–94 percentile, aspirants need a score of 70–89.
| Raw Score Range | Expected Percentile |
|---|---|
| 105–120 | 99+ |
| 90–104 | 95–98 |
| 70–89 | 90–94 |
| 50–69 | 80–89 |
| 35–49 | 70–79 |
“Candidates targeting older IIMs like Ahmedabad, Bangalore, and Calcutta typically need a 99+ percentile, whereas newer IIMs and other top B-schools often accept 95–98 percentiles.”
CAT 2024: Requirements for a Good Percentile
| Section | Number of Questions | Good Raw Score | Percentile Range |
|---|---|---|---|
| Verbal Ability and Reading Comprehension (VARC) | 24 | 36–42 | 95+ |
| Data Interpretation and Logical Reasoning (DILR) | 20 | 30–36 | 95+ |
| Quantitative Aptitude (QA) | 22 | 30–38 | 95+ |
| Total | 66 | 90–104 | 95–98 |
For aspirants wondering about the score they need to aim for, you can check out this guide on What is a Good Score in CAT? for more detailed insights.
How to Define a Good Score for Specific Colleges
| Institute | Expected Percentile for General Category | Raw Score |
|---|---|---|
| IIM Ahmedabad | 99+ | 105–120 |
| IIM Bangalore | 99+ | 105–120 |
| IIM Calcutta | 99+ | 105–120 |
| FMS Delhi | 98–99 | 100–110 |
| SPJIMR Mumbai | 95–98 | 90–104 |
| MDI Gurgaon | 94–96 | 85–100 |
“Older IIMs and institutes like FMS and SPJIMR demand higher percentiles, correlating with raw scores above 90–105. For Tier-2 B-schools, a raw score of 70–89 (90–94 percentile) is often sufficient.”
CAT 2024 Questions
1. If Rajesh’s age were to be the present age of Shivani, their age ratio would be \(3:2\). Then what would be their present age ratio?
- 2:3
- 3:2
- 4:2
- 1:2
2. Read the Passage carefully and answer the following questions.
An air conditioner (AC) unit has three operating modes: Eco, Normal, and Turbo. The power consumption in each mode is as follows: Eco mode consumes 1000 watts, Normal mode consumes 1200 watts, and Turbo mode consumes 1500 watts. Yesterday, the AC was in operation from 2 PM to 10 PM. From 2 PM to 6 PM it ran in Eco mode. From 6 PM to 8 PM, it ran in Normal mode. From 8 PM to 10 PM it ran in Turbo mode.
An air conditioner (AC) unit has three operating modes: Eco, Normal, and Turbo. The power consumption in each mode is as follows: Eco mode consumes 1000 watts, Normal mode consumes 1200 watts, and Turbo mode consumes 1500 watts. Yesterday, the AC was in operation from 2 PM to 10 PM. From 2 PM to 6 PM it ran in Eco mode. From 6 PM to 8 PM, it ran in Normal mode. From 8 PM to 10 PM it ran in Turbo mode.
3. Read the Passage carefully and answer the following questions
A health food store specializing in dietary supplements and whole grains recorded the following sales figures (in kilograms) for various food categories last month: Millets (M) = 500 kg at a cost price of 40/kg and selling price of 50/kg; Protein supplements (P) = 300 kg at a cost price of 80/kg and selling price of 100/kg; Vitamin supplements (V) = 200 kg at a cost price of 60/kg and selling price of 80/kg; Carbohydrates (C) = 600 kg at a cost price of 80/kg and selling price of 100/kg; Fats (F) = 100 kg at a cost price of 120/kg and selling price of 150/kg. Additionally, they sold 50 kg of mixed nuts (N) at a cost price of 100/kg and a selling price of 130/kg
A health food store specializing in dietary supplements and whole grains recorded the following sales figures (in kilograms) for various food categories last month: Millets (M) = 500 kg at a cost price of 40/kg and selling price of 50/kg; Protein supplements (P) = 300 kg at a cost price of 80/kg and selling price of 100/kg; Vitamin supplements (V) = 200 kg at a cost price of 60/kg and selling price of 80/kg; Carbohydrates (C) = 600 kg at a cost price of 80/kg and selling price of 100/kg; Fats (F) = 100 kg at a cost price of 120/kg and selling price of 150/kg. Additionally, they sold 50 kg of mixed nuts (N) at a cost price of 100/kg and a selling price of 130/kg
4. Analyse the bar graph carefully and answer the following questions.
5. Read the following passage and answer the questions given below:
Artificial Intelligence (AI) has transformed human life with innovations ranging from personalized recommendations to breakthroughs in healthcare and education. Despite these advances, experts warn about AI’s potential destructiveness if left unchecked. Au- tonomous systems, such as self-driving cars, could cause accidents due to unforeseen errors. Additionally, AI-powered surveillance systems pose risks to privacy and civil liberties, as governments and corporations might misuse them to monitor individuals.
One of the gravest concerns is the development of autonomous weapons, which could make life-and-death decisions without human oversight, leading to ethical dilemmas and potential large-scale harm. Furthermore, AI systems can perpetuate biases, resulting in unfair outcomes in hiring, credit allocation, and judicial decisions.
Efforts to address these concerns include the formulation of ethical guidelines, the promotion of transparency in AI systems, and the regulation of AI applications. Collab- oration between policymakers, technologists, and ethicists is crucial to ensure AI remains a force for good. However, as AI continues to evolve rapidly, striking a balance between innovation and responsibility remains an ongoing challenge.
Artificial Intelligence (AI) has transformed human life with innovations ranging from personalized recommendations to breakthroughs in healthcare and education. Despite these advances, experts warn about AI’s potential destructiveness if left unchecked. Au- tonomous systems, such as self-driving cars, could cause accidents due to unforeseen errors. Additionally, AI-powered surveillance systems pose risks to privacy and civil liberties, as governments and corporations might misuse them to monitor individuals.
One of the gravest concerns is the development of autonomous weapons, which could make life-and-death decisions without human oversight, leading to ethical dilemmas and potential large-scale harm. Furthermore, AI systems can perpetuate biases, resulting in unfair outcomes in hiring, credit allocation, and judicial decisions.
Efforts to address these concerns include the formulation of ethical guidelines, the promotion of transparency in AI systems, and the regulation of AI applications. Collab- oration between policymakers, technologists, and ethicists is crucial to ensure AI remains a force for good. However, as AI continues to evolve rapidly, striking a balance between innovation and responsibility remains an ongoing challenge.
*The article might have information for the previous academic years, which will be updated soon subject to the notification issued by the University/College.
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