NVIDIA Merlin
12
Reviews
4.5
Star rating
#13
Rank in Machine Learning
Pros and cons
Pros
- Scalability
- Ease of Use
- Reliability
- Quality
- Deployment Ease
- Easy Setup
Cons
- Expensive
- Slow Performance
- Poor Documentation
- Limited Features
- Inefficient Translation Management
- Difficult Learning
Traffic & LLM citations
Source: G2 review data
Winning from
Key stats
-100.0%
67
Small Business
1
Adoption by company size
| Segment | Share of reviews |
|---|---|
| Small Business | 54.5% |
| Mid-Market | 27.3% |
| Enterprise | 18.2% |
Quarterly history
| Quarter | Reviews | Star rating |
|---|---|---|
| 2024 Q4 | 3 | 4.8 |
| 2025 Q1 | 3 | 4.2 |
| 2025 Q2 | 2 | 5.0 |
| 2025 Q3 | 1 | 4.5 |
| 2025 Q4 | 1 | 4.0 |
| 2026 Q2 | 2 | 4.5 |
Satisfaction ratings
Ease of Use9.4
Ease of Setup9.2
Quality of Support9.3
Meets Requirements9.4
What reviewers say
Fast, Scalable Recommendation Systems That Save Development Time
4.0
“What I like best about NVIDIA Merlin is how easily it helps build powerful recommendation systems—it’s fast, scalable, and saves a lot of development time.”
NVIDIA Merlin
4.5
“Merlin's GPU Acceleration is quite faster. It is modular interconnected. It provides end to end framework.”
Good platform to develop recommender system
4.5
“Merlin's processing speed is outstanding. We can utilize the GPU to process large datasets and perform many experiments quickly.”