Blind 75 vs. LeetCode patterns: Strategy for NVIDIA interviews
You have probably used ChatGPT, played a graphics-heavy video game, or read about breakthroughs in self-driving cars. What do all of these have in common? NVIDIA. While the spotlight often shines on apps and AI tools, it is NVIDIA’s GPUs quietly powering them behind-the-scenes.
The scale is staggering. Training a single large AI model can take thousands of NVIDIA GPUs running for weeks. Multiply that across the dozens of models being trained worldwide, and you start to see how central NVIDIA is to modern innovation. Their technology serves as the driving force behind the AI revolution, accelerates scientific research, and powers the experiences millions around the globe use every day.
To be part of such a competitive company, you need to walk into the interviews fully prepared. With so many resources and guides available, the question is which approach will get you ready: Blind 75, NVIDIA’s Top 75 questions, or the broader set of LeetCode patterns?
Grokking the Coding Interview Patterns
With thousands of potential questions to account for, preparing for the coding interview can feel like an impossible challenge. Yet with a strategic approach, coding interview prep doesn’t have to take more than a few weeks. Stop drilling endless sets of practice problems, and prepare more efficiently by learning coding interview patterns. This course teaches you the underlying patterns behind common coding interview questions. By learning these essential patterns, you will be able to unpack and answer any problem the right way — just by assessing the problem statement. This approach was created by FAANG hiring managers to help you prepare for the typical rounds of interviews at major tech companies like Apple, Google, Meta, Microsoft, and Amazon. Before long, you will have the skills you need to unlock even the most challenging questions, grok the coding interview, and level up your career with confidence. This course is also available in JavaScript, Python, Go, and C++ — with more coming soon!
In this blog, I will show you how Blind 75 and NVIDIA’s Top 75 stack up against the 28 LeetCode patterns from the Grokking the Coding Interview Patterns course. More importantly, I will help you build an NVIDIA coding interview prep strategy for 2025 that goes beyond problem lists and trains you to think in patterns, just like NVIDIA engineers solving real-world challenges.
A quick recap: Blind 75, NVIDIA Top 75, and LeetCode patterns#
Blind 75 is a curated list of 75 well-known LeetCode problems that cover the most common data structures and algorithms. Arrays, strings, linked lists, graphs, and dynamic programming are all part of this set, making it a popular starting point for many candidates.
NVIDIA Top 75 is a set of the most frequently asked coding questions in NVIDIA interviews. This list highlights problem areas that have repeatedly come up in recent interview cycles and offers insight into the types of challenges candidates have faced at the company.
LeetCode patterns is a framework of 28 core problem-solving strategies that group problems by their underlying approach. Examples include Sliding Window, Dynamic Programming, Graph Traversal, and Backtracking. By learning these, you train yourself to recognize the structure behind a wide range of problems.
Does Blind 75 really prepare you for NVIDIA?#
In today’s world, AI is everywhere. OpenAI works to keep its models current, but companies like NVIDIA build the technology enabling tomorrow’s breakthroughs. That same spirit of constant progress can also be seen in their interviews. NVIDIA has the ability to introduce fresh variations of problems rather than relying only on the familiar ones that candidates might expect.
If that is the case, then preparing only with a static list of 75 questions, especially one created years ago, will not be enough. Blind 75 can, on the other hand, give you a foundation, but this means that excelling at NVIDIA requires going beyond checklists and building the adaptability to solve new challenges.
Will LeetCode patterns take you through NVIDIA interviews?#
LeetCode patterns can make a big difference when preparing for NVIDIA. Instead of practicing random problems, patterns teach you to recognize the underlying strategies that keep showing up.
For NVIDIA, this approach is especially valuable because its interviews are not limited to straightforward implementations. Problems may combine multiple concepts or require you to push an idea further, like optimizing a graph traversal, handling large data efficiently, or extending a dynamic programming solution. Recognizing patterns allows you to break these problems down systematically, rather than feeling stuck when the question takes an unexpected turn.
By studying patterns, you build the ability to adapt when a problem looks new on the surface, but shares more or less the same structure as something you have solved before. This adaptability is exactly what helps you feel confident in NVIDIA interviews, where variations of problems are common.
An overview of patterns for NVIDIA coding interviews#
As there are 28 patterns in total, it helps to know where to start. Based on the frequency of NVIDIA’s Top 75, the patterns can be grouped into four clear categories.
Must-know patterns are the ones you will see most often in NVIDIA interviews. They form the foundation of your prep and should be mastered first.
High-value patterns show up regularly enough to matter and add important depth to your preparation.
Solid but situational patterns appear less often, but strengthen your ability to handle variety when the questions shift.
Finishing-line helpers are rare, yet covering them ensures you reach full coverage and are not surprised by an unexpected twist.
NVIDIA interviews may place more weight on some patterns than others, but the best preparation still covers all 28. This ensures you are ready for the most frequent problem types while also building the flexibility to tackle unexpected variations.
The NVIDIA prep roadmap with all 28 patterns#
The smartest way to prepare for NVIDIA is to balance efficiency with completeness. I recommend the four-step roadmap outlined below.
Start with the overlap: Begin with the problems that appear in both Blind 75 and NVIDIA’s Top 75. These cover core computer science topics that are essential everywhere, and directly relevant to NVIDIA.
Move to NVIDIA-specific problems: Next, work through the remaining NVIDIA Top 75. These highlight the unique challenges NVIDIA emphasizes and give you a sense of the company’s problem style.
Practice the rest of Blind 75: Then, solve the Blind 75 problems that do not overlap with NVIDIA’s list. They expand your fundamentals and often fill gaps in your pattern coverage.
Strengthen the remaining patterns: Finally, close the loop by focusing on any patterns not fully covered yet. This step prepares you for unseen variations and ensures you walk in with complete coverage.
As you move through this roadmap, keep the rubric and scoring method from earlier in the series in mind. The goal is not just to check off coding problems but to build real depth across every pattern. For each pattern, aim to solve one easy coding problem for 1 point, two medium problems for 8 points total (4 each), and one hard problem for 6 points. This gives you a pattern score of 15 points per pattern. Reaching this level across all 28 core patterns adds up to an ideal total of 420 points, which represents complete and confident readiness for NVIDIA coding interviews.
If you want to understand the 1–2–1 rubric and LeetCode pattern scoring framework in detail, check out my first blog in this series, Blind 75 vs LeetCode patterns: Which wins coding interviews?. It explains how this approach measures depth, tracks your progress across patterns, and helps you reach full interview readiness.
This balanced and data-driven approach keeps your preparation efficient and comprehensive. It helps you strengthen your fundamentals while building the problem-solving depth NVIDIA interviewers look for.
Start with overlapping patterns#
Starting with the overlap makes your prep both efficient and relevant, enabling a focused approach to preparation. These problems cover the computer science fundamentals that every interviewer expects, while also giving you direct exposure to questions NVIDIA has asked before. It is a practical way to build momentum and set a solid base for the next stages of preparation.
Let’s put Blind 75 and NVIDIA’s Top 75 side by side to see how much overlap there is.
Blind 75 (Problem Name) | NVIDIA 75 (Problem Name) |
Last Stone Weight | |
LRU Cache | |
Special Binary String | |
Dot Product of Two Sparse Vectors | |
Add Two Numbers | |
Move Zeroes | |
Merge Two Sorted Lists | Task Scheduler II |
Minimum Operations to Reduce an Integer to 0 | |
Fibonacci Number | |
String to Integer (atoi) | |
Trapping Rain Water | |
Unique Paths II | |
Copy List with Random Pointer | |
Reverse Words in a String | |
Palindromic Substrings | Find the Duplicate Number |
Insert Delete GetRandom O(1) | |
Break a Palindrome | |
Max Sum of a Pair With Equal Sum of Digits | |
Longest Repeating Character Replacement | 4Sum |
Reverse Linked List II | |
Combination Sum | Intersection of Two Linked Lists |
Kth Largest Element in an Array | |
Maximal Square | |
Reorder List | Rectangle Area |
H-Index | |
Maximum Product Subarray | Snapshot Array |
Sum of Two Integers | Remove Stones to Minimize the Total |
Reverse Integer | |
Generate Parentheses | |
Lowest Common Ancestor of a Binary Search Tree | Minimum Path Sum |
Number of Connected Components in an Undirected Graph | Max Points on a Line |
Majority Element | |
Best Time to Buy and Sell Stock IV | |
Course Schedule II | |
Verify Preorder Sequence in Binary Search Tree | |
Non-overlapping Intervals | Intersection of Two Arrays |
Meeting Rooms | Linked List Random Node |
Shuffle an Array | |
Maximum Depth of Binary Tree | Convert Binary Search Tree to Sorted Doubly Linked List |
Encode and Decode Strings | Single Element in a Sorted Array |
Design HashMap | |
Find Pivot Index | |
Sliding Puzzle | |
Same Tree | Minimum Add to Make Parentheses Valid |
Delete Duplicate Folders in System | |
Construct Binary Tree from Preorder and Inorder Traversal | Maximum Sum of Distinct Subarrays With Length K |
Invert Binary Tree | Maximize Greatness of an Array |
Graph Valid Tree | Longest Common Prefix |
Subtree of Another Tree | Valid Sudoku |
The list above shows that there are 26 problems that overlap between Blind 75 and NVIDIA’s Top 75, which amounts to about 35%. That is a solid starting point, as more than a third of your preparation can be streamlined by focusing on problems that matter in both lists. It gives you efficiency early on while also ensuring that you are covering the fundamentals NVIDIA values in its interviews.
Now, let’s break down how well the overlapping problems cover the patterns when we apply the 1–2–1 rubric. In the bar chart below, each bar represents a pattern. The length of the bar shows what percent of the full 15 points you’ve earned for that pattern, while the label highlights how many easy, medium, and hard problems went into that score.
The bar chart above shows that you are offered an exposure to 16 out of 28 patterns, which is about 57% coverage. That’s more than half of the core problem-solving strategies. Some patterns, like Tree Depth-first Search and Dynamic Programming, already have partial depth, while others are introduced with just one problem.
The key is that each pattern counts. Even light coverage is valuable because it gives you a starting point. Using the 1–2–1 rubric, you can turn this exposure into full mastery by practicing one easy, two medium, and one hard problem for every pattern. This way, the 57% overlap, becomes a springboard for building depth and confidence.
Next: Solve NVIDIA-specific questions #
These questions help you align your preparation with what matters most at NVIDIA to make your practice more targeted. They give you a sense of the company’s problem style while also adding variety to your prep. Each one builds on the foundation you set with the overlap, bringing you a step closer to complete readiness.
Let’s see what new patterns this set of questions brings to the table:
Pattern Name |
The list above shows that this step introduces 10 new patterns, which takes your total coverage to 26 out of 28 patterns, that’s about 93%. Reaching this level is a major milestone, because it shows how much value NVIDIA-specific questions add. Not only do they expand your pattern coverage, but they also bring you much closer to complete readiness. It is one of the most impactful steps in the entire prep journey.
Now, let’s look at how these patterns stack up when measured against the 1—2—1 rubric. The bar chart below highlights the newly covered patterns in green on the y-axis:
The bar chart above shows that this set of NVIDIA-specific questions reflects significant progress. Many of the patterns you were previously exposed to are now more thoroughly covered, with several, such as Two Pointers, Greedy Techniques, Dynamic Programming, and Tree Depth-First Search, reaching coverage levels above 90%. At the same time, new patterns such as Math and Geometry, Hash Maps, and Custom Data Structures have been added to the mix as they offer a solid starting coverage.
A few patterns remain lighter at this stage, but the rubric makes it clear how to close those gaps by adding one easy, two medium, and one hard problem per pattern. Each new step enhances your adaptability and brings you closer to full preparedness.
How will the remaining Blind 75 help?#
This step pushes your preparation beyond company-specific trends and into broader problem-solving territory. These problems often fill in gaps by introducing patterns you may not have encountered yet, while also reinforcing the fundamentals across multiple categories. This step ensures you are not only ready for NVIDIA, but also well-prepared for any unexpected variations in interviews.
Let’s see which new patterns get unlocked when you practice the Blind 75–specific questions:
Pattern |
The list above shows that this final set introduces 2 completely new patterns, which takes the total coverage to a full 100%. Hitting complete coverage is a huge milestone because it means you now have exposure to every major problem-solving framework that could show up in NVIDIA’s interviews.
Let’s quickly see how well these patterns are covered according to the rubric.
The bar chart above shows that the progress is consistent and balanced. With Trie already at 100% coverage, several other patterns, such as Sliding Window, Topological Sort, and Graphs, are nearing completion. Each requires just one straightforward problem to reach full coverage.
At the same time, patterns such as Merge Intervals, In-place Manipulation of a Linked List, Knowing What to Track, and Bitwise Manipulation are partially covered, which means they also just need a few more problems to reach completion. A handful of patterns, including Union Find, K-way Merge, and Backtracking, remain underrepresented, but these are exactly the gaps you can bridge by applying the rubric method. Solving one easy, two mediums, and one hard for each.
Overall, this stage shows real momentum: many of the core patterns are already locked in, and with a bit of targeted focus, the remaining ones can be brought up to full coverage as well.
Are you NVIDIA ready yet?#
Let’s look at the following bar chart to gain a comprehensive view of your coverage across all 28 patterns under this strategic study plan, and identify the areas that still require your attention.
This overall view shows impressive progress: 9 patterns are already at 100% coverage and another 4 are above 90%. This means nearly half of the patterns are essentially mastered. Around 6 patterns sit in the 60–89% range, requiring just a bit more practice to reach full strength. The remaining 9 patterns are still under 60%, with a couple like Cyclic Sort and Backtracking at the lower end.
The best part is that every pattern is at least introduced, so nothing is left completely uncovered.
The takeaway is clear: most of the groundwork is already solid, and now the focus should shift to closing the gaps in those underrepresented patterns. By applying the rubric (1 easy, 2 medium, 1 hard), you can steadily bring each of those patterns up to full coverage, pushing toward complete mastery.
Patterns recap#
The progression of pattern coverage shows how each stage builds on the last to create a complete strategy. Starting with the overlapping set gives you 57.1% coverage, which means more than half of the patterns are already addressed right at the beginning. Incorporating NVIDIA-specific problems marks a major leap forward, contributing another 35.7% and ensuring your prep reflects the company’s unique challenges. Finally, the remaining 7.1% comes from Blind 75 alone, which fills in the last few gaps so that no core area is left uncovered. Step-by-step, this approach brings you to full coverage across all 28 patterns.
How close does this strategy get you to 420 points?#
If we look at the score breakdown, it can be clearly seen how progress builds step-by-step. The overlapping set gives you 77 points, setting a solid base early on. Incorporating the NVIDIA-specific problems provides the biggest boost with 120 points, showing how much value company-tailored prep brings. The remaining Blind 75 problems contribute 69 points, pushing the total to 266 points.
That leaves 154 points still on the table, which can be earned by going deeper into each pattern with the rubric’s structure of one easy, two medium, and one hard problem. Following this framework is what will take you from a steady head start to the full 420-point target.
Wrapping up: What matters most for NVIDIA interviews#
Interview prep for NVIDIA is about proving you can think like an engineer who builds technology that powers the future of AI, graphics, and computing. Lists like Blind 75 or NVIDIA’s Top 75 are useful, but the real advantage comes from learning patterns and applying them to a variety of problems. That is what prepares you for the unexpected.
Remember, NVIDIA’s work touches almost every corner of modern innovation, from AI breakthroughs to high-performance computing. The more versatile your preparation, the more you mirror the adaptability their teams demonstrate every day. If you focus on mastering patterns and practicing with intent, you will not just be ready for the interview, you will be ready to thrive at NVIDIA.
Recommended resources to level up your interview prep#
While this blog gives you a data-driven way to measure and close your prep gaps, the right learning tools can accelerate your progress even further. Here are two highly effective resources to complement your study plan:
Educative’s personalized interview prep: It’s your tailored prep companion that adapts to your skill level, and focuses on the 28 essential LeetCode patterns we’ve been discussing. You can work on the patterns that need the most attention, track progress with clear metrics, and know exactly what to tackle next. Whether it’s adding an easy problem to build confidence or a hard one to push for mastery, you’ll always be working on the right problems at the right time.
Educative’s mock interviews: Practicing is not just about solving problems. It is also about handling real interview pressure. Educative’s AI mock interviews let you simulate actual interview conditions, get actionable feedback, and improve in areas like problem-solving speed. This way, you are not only technically prepared but also confident and ready to perform under time constraints.
