Grind 75 vs. LeetCode patterns: Roadmap for NVIDIA interviews

In the race to secure an offer at NVIDIA—a company at the forefront of AI and modern computing—the most limited resource is time. Every hour of preparation needs to contribute directly to interview performance, and time spent on the wrong material can mean missed opportunities. The central challenge for aspiring NVIDIA engineers is clear: with so many coding interview prep resources available, which ones actually reflect NVIDIA’s expectations and prepare candidates effectively?

While plenty of coding interview prep guides exist, they primarily focus on long-established big tech players like Meta, Google, Amazon, and other FAANG companies. NVIDIA, however, has quickly risen to join their ranks as one of the most influential forces in tech. This shift makes it critical to rethink your NVIDIA interview prep and choose the roadmap that maximizes your success chances.

So, what’s the smarter choice for NVIDIA interviews: practicing curated problem lists like Blind 75 or Grind 75, or understanding the underlying LeetCode patterns that power every coding problem?

In this blog, I’ll show how Grind 75 and NVIDIA’s Top 75 stack up against the 28 LeetCode patterns from Grokking the Coding Interview Patterns and how you can build a smarter NVIDIA interview prep roadmap that reflects the company’s unique hardware–software fusion.

Sneak peek: How we evaluated NVIDIA interview prep strategies

The challenge with comparing different interview prep resources is that they all promise efficiency in different ways. Some consider Blind 75 the gold standard for coding interview prep, while others prefer NeetCode 150. To make this analysis fair and practical, I used a clear scoring rubric, first introduced in the opening blog of this series, “Grind 75 vs. LeetCode Patterns: Most Effective for Interviews?”. Let’s quickly revisit that rubric.

For a coding pattern to be considered well-covered, the set must include at least one easy problem worth 1 point, two medium problems worth 8 points (4 each), and one hard problem worth 6 points. That makes 15 points per pattern. With 28 patterns in total, the maximum score is 420 points. The closer your prep strategy gets to this benchmark, the more complete and reliable it is for NVIDIA interviews.

Now that we have this benchmark, let’s see how Grind 75 and NVIDIA’s top 75 perform against it.

The chart above makes one clear: the NVIDIA-focused roadmap performs significantly better than relying on Grind 75 or even NVIDIA’s top 75 alone. But what exactly is this roadmap, and why does it cover more ground? That’s the question we’ll answer in the sections ahead.

We’ll go beyond the numbers to see which LeetCode patterns drive these scores, how well each pattern is covered under the 1–2–1 rubric, and what it takes to close the remaining 38% gap to reach complete NVIDIA interview readiness.

Grind 75, NVIDIA top 75, and LeetCode patterns: Quick overview#

What is Grind 75? It’s an extended and improved version of the well-known Blind 75 list of LeetCode problems. Grind 75 curates 75 carefully selected questions from the broader Grind 169, covering key topics such as arrays, linked lists, and trees.

What is NVIDIA top 75? It is a list compiled from questions frequently asked in NVIDIA coding interviews, per LeetCode. It brings in company-specific variations and reflects the problem-solving style NVIDIA interviewers prefer.

What are LeetCode coding patterns? LeetCode patterns are fundamental problem-solving strategies that commonly appear in coding interviews. Each pattern represents a reusable way to tackle a class of problems, regardless of the specific question. They are the building blocks behind most interview challenges and provide a structured way to understand how problems connect. There are a total of 28 core coding patterns, and a few common patterns include:

• Two Pointers, where two indexes move inward or outward to find pairs or subarrays.

• Sliding Window, which efficiently finds subarrays or substrings that meet certain conditions.

• Binary Search, used when searching over a range of possible results rather than directly in an array.

Is Grind 75 all you need for NVIDIA coding interviews?#

No. While Grind 75 does a good job covering the fundamentals and many conventional topics, it doesn’t fully capture the nuances of NVIDIA coding interviews.

NVIDIA is relatively new in the league of highly influential tech companies, yet it already has a large footprint on LeetCode with almost 140 tagged questions. This reflects NVIDIA’s growing importance and the reality of their interview process: the problems evolve. As the company powers AI and high-performance computing breakthroughs, its interview questions increasingly feature new twists and variants.

Grind 75, by contrast, was created several years ago with a primary focus on FAANG companies. If you rely on it alone, you risk missing the unique problem styles NVIDIA is known to introduce.

To put the gap into perspective, if we look at NVIDIA’s 10 most frequently asked coding questions on LeetCode, 5 don’t even appear in Grind 75 (highlighted in green in the table below). That’s half of the top questions missing, and with AI making it easier than ever to generate new problem variations, this gap is only likely to grow.

Are LeetCode patterns the key to cracking NVIDIA coding interviews?#

The short answer is yes.

Where static lists like Grind 75 fall short, LeetCode Patterns provide the flexibility NVIDIA interviews demand. Unlike a fixed list created years ago, patterns don’t go out of date. They represent 28 problem-solving strategies that form the foundation of almost every coding question you’ll encounter.

This distinction is especially important for NVIDIA. The company already has close to 140 interview questions tagged on LeetCode, and that number keeps growing as new problem variants appear. Instead of trying to memorize every possible question, learning patterns equips you to recognize the underlying structure and solve both familiar and unfamiliar problems with confidence.

To put this into perspective, even if a question doesn’t show up on Grind 75 or NVIDIA’s top 75, chances are it still maps back to one of these 28 patterns. That’s why patterns give you an edge. They help you prepare for the known while staying ready for the unexpected.

Reviewing LeetCode patterns for NVIDIA coding interviews#

While LeetCode patterns are crucial for passing NVIDIA coding interviews, having all 28 in front of you can feel overwhelming. The real question becomes: where should you start? To make this practical, I’ve grouped the patterns into four categories:

• Must-know patterns: These patterns are the most frequently tested in NVIDIA coding interviews. Covering them is essential, because many interview problems are built directly around these strategies.

• Very common patterns: These show up often enough that practicing them will give you a clear advantage. They may not dominate the interviews, but they recur consistently and are too valuable to ignore.

• Solid but situational patterns: These patterns appear less frequently, but when they do, recognizing them quickly can set you apart. Solving them under time pressure signals strong breadth in your preparation.

• Finishing-line helpers: These are the least common patterns for NVIDIA. They rarely surface, yet being prepared here ensures you don’t carry any gaps into the interview room.

Even though certain patterns appear more frequently in NVIDIA coding interviews, the best way to prepare is to cover all 28. This ensures you build depth in the patterns NVIDIA tests most often, without leaving gaps in the less frequent ones that can still appear in interviews.

NVIDIA coding interview roadmap#

To prepare effectively for NVIDIA coding interviews, you need a roadmap that balances efficiency with completeness. By combining Grind 75, NVIDIA’s top 75, and the 28 LeetCode patterns, we can build a structured plan that ensures all 28 patterns are covered in less time. Here’s how to approach it step by step:

1. Begin with the Grind 75-NVIDIA overlap: Start with the questions that appear in both Grind 75 and NVIDIA’s top 75. This overlap represents the strongest common ground: problems that are both frequently asked and NVIDIA-relevant. Covering these first ensures your initial effort builds a foundation aligned with NVIDIA’s interviews.

2. Tackle NVIDIA-only questions next: Once the overlap is complete, move to the problems unique to NVIDIA’s top 75. These capture NVIDIA’s distinct interview style and highlight variations that aren’t reflected in general prep sets.

3. Work through the remaining Grind 75 problems: After covering the overlap and NVIDIA-specific sets, return to finish the rest of Grind 75. These problems solidify your understanding of core data structures and algorithms. Even if they aren’t asked exactly as written, the concepts they reinforce show up repeatedly in NVIDIA interviews.

4. Close the gaps with pattern-based practice: Finally, measure your progress against the 28 LeetCode patterns. Any pattern still not covered becomes your focus for targeted practice.

Follow this prep plan using the 1–2–1 rubric and scoring method. This makes your NVIDIA coding interview preparation both efficient and complete: you address the company’s unique priorities while ensuring all 28 patterns are in your toolkit.

Why start with the Grind 75-NVIDIA overlap?#

Starting with the Grind 75-NVIDIA overlap gives you an immediate advantage because these problems have already been validated by two independent sources: they are both frequently asked in general top-tech interviews and specifically tagged for NVIDIA. That double confirmation means you are not wasting effort on low-value problems. This ensures your first phase of prep is both efficient and strategically aligned with NVIDIA’s priorities.

Let’s look at the Grind 75 and NVIDIA’s top 75 side by side to identify the overlapping coding problems:

The comparison above shows that 20 coding problems are common to both Grind 75 and NVIDIA’s top 75. That’s an encouraging beginning for NVIDIA interview prep. Now, let’s examine which patterns these overlapping problems cover, and how well they hold up against 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.

Note: For this calculation, I have only considered the counts that satisfy our 1–2–1 rubric. If a pattern has more questions than required by the rubric, I count only 1 easy, 2 medium, and 1 hard problem. For example, if Dynamic Programming has 10 medium questions, I have included just 2 in this calculation.

The bar chart above shows that this first step introduces 15 out of the 28 patterns (about 53%), which is a major milestone so early in the roadmap. Among these, Two Pointers and Tree Depth-First Search already reach partial coverage, showing strong early traction in high-frequency areas. Other patterns, like Heaps, Dynamic Programming, and Sliding Window, are present but remain underrepresented, giving you visibility into where further practice will be needed.

In other words, the overlap immediately exposes you to more than half of the core coding patterns, laying a broad foundation while pointing out the gaps you’ll need to close in later stages.

Why move to NVIDIA-only problems next?#

Focusing on the NVIDIA-only problems right after the overlap ensures your prep is aligned with the company’s unique interview style. These questions capture the variations that don’t appear in more general lists like Grind 75. Practicing them early gives you exposure to NVIDIA’s distinct problem style, ensuring you are prepared when interviewers introduce variations that extend beyond conventional lists.

Let’s look at the patterns introduced by NVIDIA-specific coding problems:

The list above shows that NVIDIA-only coding problems introduce 11 new patterns, bringing the total to 26 out of 28. That is 93% coverage, a big step forward and a clear sign that the NVIDIA prep roadmap is moving in the right direction.

Now, let’s see how well these patterns are covered under 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 adding the NVIDIA-only problems significantly strengthens your pattern coverage. Some of the patterns introduced in the overlap step, such as Two Pointers, Dynamic Programming, and Greedy Techniques, are now fully covered. Tree Depth-First Search also advances to 93% coverage, showing that NVIDIA-specific questions reinforce many of the most common strategies.

This stage also brings in new patterns that were missing earlier, including Math and Geometry, and Hash Maps, both of which are important for NVIDIA interviews.

Some coding patterns remain underrepresented, such as Cyclic Sort, Bitwise Manipulation, and Top K Elements, but the roadmap now spans almost the entire set of patterns, making it one of the most complete stages of preparation. With 1–2–1 rubric in hand, you can easily complete these patterns.

Why finishing the rest of Grind 75 matters#

Completing the rest of Grind 75 ensures your fundamentals are fully reinforced. While the overlap and NVIDIA-only sets cover most patterns, some core areas of data structures and algorithms are still underrepresented. This step rounds out your practice with balanced exposure to arrays, linked lists, trees, graphs, and other coding patterns that NVIDIA interviewers still value.

The impact is twofold. First, it helps strengthen partially covered patterns by giving you the missing easy, medium, or hard problems needed to meet the 1–2–1 rubric. Second, it reduces weak areas by filling gaps in foundational topics that could otherwise trip you up in a high-pressure interview setting.

Let’s see which patterns are added by the remaining Grind 75 problems:

The list above shows that the Grind 75–only coding problems introduce 2 new patterns, bringing the total to 28 out of 28. That is complete coverage, a full 100%. This is an amazing outcome.

Now, let’s see how well each pattern in this set is covered under the 1–2–1 rubric.

The bar chart above shows that several patterns that were introduced earlier are now strengthened. For example, Math and Geometry and Sliding Window move into the well-covered zone. Other important patterns such as Graphs, Hash Maps, and Modified Binary Search rise into partial coverage.

At the same time, this stage introduces Tree Breadth-First Search and Backtracking, the final missing patterns, and bring it onto the board along with reinforcement for less common ones like Fast and Slow Pointers.

Is your NVIDIA coding interview prep complete now?#

Let’s analyze a high-level view of the overall roadmap progress, and what’s required for the complete preparation.

The bar chart above shows that at this stage, 8 out of 28 patterns are in the green zone, i.e., well covered. These include some of the most important strategies for NVIDIA interviews, such as Two Pointers, Dynamic Programming, Greedy Techniques, and Tree Depth-First Search.

Another 7 patterns are in the yellow zone, i.e., partially covered, including Heaps, Graphs, Hash Maps, and Modified Binary Search. Most of these need just one hard or two medium coding problems to cross into the fully covered zone.

The remaining 14 patterns are still in the red zone, i.e., underrepresented. Closing these gaps requires targeted practice, typically 2–3 problems per pattern to hit the 1–2–1 benchmark. Many of these are less frequent patterns, but leaving them underprepared introduces oversights that can be costly in a real interview.

The good news is that no pattern is missing anymore. All 28 are now represented, and with deliberate practice, you can move everything into the green zone.

Patterns recap for NVIDIA coding interview prep#

Let’s look at a clear snapshot of overall progress in terms of how many patterns were covered across the different stages of this NVIDIA-focused roadmap.

Looking at the overall breakdown, the common patterns between Grind 75 and NVIDIA’s top 75 contribute the most, covering more than half of the total patterns (53.6%). This overlap alone gives you a strong starting base and explains why it is the most valuable first step in the roadmap.

The NVIDIA-only problems add another 39.3%, almost completing the set. This shows how critical company-specific questions are for reaching near-full coverage and aligning with NVIDIA’s interview style.

Finally, the remaining Grind 75 problems contribute 7.1%, but that small slice makes a big difference: it brings the roadmap to 100% pattern identification. Without this step, you would still have gaps in preparation.

This staged contribution is exactly what makes the roadmap effective. You start broad with common ground, build depth with NVIDIA-specific problems, and finish strong with the remaining Grind 75 to ensure complete coverage of all 28 patterns.

Score breakdown for NVIDIA coding interview prep#

So far, we’ve looked at pattern coverage, but how does this translate into measurable progress? The score chart below shows how many points each stage of the NVIDIA-focused roadmap contributes toward the 420-point benchmark, making it clear where most of the progress comes from and what still remains.

The score breakdown highlights how each stage contributes toward the 420-point benchmark. The NVIDIA-only problems add the largest share with 128 points, showing why company-specific practice is so valuable. The common overlap between Grind 75 and NVIDIA contributes 69 points, giving you an efficient foundation at the start. The remaining Grind 75 problems add another 64 points, rounding out the fundamentals and ensuring no core areas are missed.

Together, these stages bring you to 261 points, or 62% of the total benchmark. That is substantial progress, and more importantly, it is distributed in a way that balances NVIDIA-specific depth with broad pattern coverage. The remaining 159 points can now be targeted directly by filling gaps in underrepresented patterns using the 1–2–1 rubric, making your prep both efficient and complete.

Wrapping up: Grind 75 or LeetCode patterns for NVIDIA interviews?#

If there’s one takeaway from this analysis, it’s that no single list is enough for NVIDIA coding interviews. Grind 75 provides a solid foundation, but it was never designed with NVIDIA in mind. NVIDIA’s top 75 brings the company’s unique flavor, yet by itself it doesn’t ensure complete coverage. And, while LeetCode Patterns give you the adaptability to solve new problems, they need to be tied to real practice questions to deliver results.

The most effective strategy is a hybrid roadmap: start with the Grind 75-NVIDIA overlap, move to NVIDIA-only problems, complete the rest of Grind 75, and finally close gaps with the 28 patterns using the 1–2–1 rubric. This way, your prep is both efficient and complete: you avoid redundancy, strengthen the must-know patterns, and cover every angle NVIDIA interviews demand.

At the end of the day, your goal isn’t just to solve a fixed set of questions, but to walk into an NVIDIA interview with confidence that whatever problem you see, you’ve already built the pattern-based skills to solve it. Good luck!

Recommended resources to level up your NVIDIA interview prep#

While this blog offers 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.