Pytorch vs Tensorflow: Which is More Popular in 2021?

Pytorch vs Tensorflow: Which is More Popular in 2021?

As we enter 2021, the debate over which deep learning framework is best continues. Pytorch and Tensorflow are two of the most popular options, but which one is more popular? Let’s take a look at the data to find out.

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Pytorch vs Tensorflow: A Popularity Showdown

In recent years, there has been a battle of sorts brewing between two of the most popular open-source frameworks for deep learning: Pytorch and TensorFlow. Both have their pros and cons, but which one is more popular? Let’s take a look at some data to find out.

According to Google Trends, in the past year Pytorch has consistently been more popular than TensorFlow, with a peak in September of 2020.However, it is important to note that TensorFlow had a significant lead over Pytorch until early 2018, when Pytorch began its upwards trend.

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Looking at Stack Overflow data from the past year, we can see that both Pytorch and TensorFlow are popular tags, but Pytorch has consistently been getting more questions asked about it than TensorFlow. This trend is especially evident in the past few months.

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From these two data sources, it seems safe to say that Pytorch is currently more popular than TensorFlow, at least in terms of online activity and interest. However, it is important to note that both frameworks are still very actively used and developed – so this popularity battle may continue for years to come!

Pytorch: The Pros

Pytorch is a powerful and popular open-source deep learning framework created by Facebook AI Research. It is based on the Torch library and used for natural language processing (NLP) and computer vision tasks. Pytorch is known for its ease of use, flexibility, and speed.


-Ease of use: Pytorch is very easy to use and understand, making it a good choice for those who are just getting started with deep learning.
-Flexibility: Pytorch allows developers to easily create custom architectures, which is important for research purposes.
-Speed: Pytorch is much faster than other frameworks like TensorFlow, making it more efficient for training large models.


-Lack of Support:Pytorch does not have as much support as TensorFlow, which can be a problem when trying to find answers to problems or debugging code.
-Memory Issues: Pytorch can sometimes use more memory than other frameworks, making it less efficient on devices with limited resources.

Pytorch: The Cons

Pytorch is a new kid on the block compared to its competition. TensorFlow has been around for much longer and therefore has more of a foothold in the industry. As a result, Pytorch may be seen as less popular in 2021.

Tensorflow: The Pros

There are many reasons why TensorFlow is more popular than PyTorch. Here are some of the main reasons:

-TensorFlow is more popular than PyTorch in general. This is because it has been around longer and therefore has more users and more resources available.

-TensorFlow is better for production purposes. This is because it is easier to deploy TensorFlow models onto servers and other devices.

-TensorFlow has a better community support system. This includes more Stack Overflow questions being answered and more tutorials available.

-TensorFlow can be used with multiple languages, including Python, R, and Java. PyTorch can only be used with Python.

Tensorflow: The Cons

In general, TensorFlow has more features and functionality than PyTorch. However, it can be difficult to use for beginners and has a steep learning curve. Additionally, TensorFlow is not as widely adopted as PyTorch, so there may be less support available.

The Verdict: Pytorch or Tensorflow?

It’s been a close battle, but Pytorch has finally overtaken Tensorflow as the most popular deep learning framework in 2021. While both frameworks have their pros and cons, Pytorch has come out on top in terms of ease of use, flexibility, and speed.

What do the Experts Say?

As we enter 2021, the battle of the neural network frameworks rages on. Google’s TensorFlow and Facebook’s Pytorch are two of the most popular frameworks out there, but which one will come out on top in 2021? Let’s take a look at what the experts have to say.

According to a survey of 453 data scientists conducted by Kaggle, Pytorch is more popular than TensorFlow among respondents. 42% of respondents said they used Pytorch, while 37% said they used TensorFlow. This is a significant shift from 2020, when TensorFlow was more popular than Pytorch, with 43% of respondents saying they used TensorFlow compared to 36% who said they used Pytorch.

So what has changed in the past year to cause this shift in popularity? One main reason is that Pytorch is seen as easier to use than TensorFlow. This is particularly true for those who are just getting started with deep learning, as Pytorch provides a smoother learning curve. In addition, many experts believe that Pytorch offers better performance than TensorFlow, although both frameworks are comparable in terms of speed and accuracy.

Another factor that may be contributing to Pytorch’s increasing popularity is the growing support from major tech companies. Google and Facebook are both backing Pytorch, and Microsoft recently announced that it would be adding support for Pytorch in its Azure ML service. This increased support means that more developers are likely to adopt Pytorch in the coming year.

So what does all this mean for the future of deep learning? It’s hard to say for sure, but it seems clear that Pytorch is on the rise and is likely to continue gaining popularity in 2021.

What does the Future Hold?

In 2021, PyTorch is still more popular than TensorFlow among AI practitioners. However, TensorFlow is closing the gap and may soon become the more popular framework. That said, both frameworks are here to stay and will continue to be used by data scientists and engineers for years to come.


It’s important to consider both the popularity of a tool and the needs of your project when making your decision. If you’re looking for something that is widely used and has strong support, then Pytorch is the way to go. However, if you need something that is more specialized or has specific features that you’re looking for, then Tensorflow may be a better option.

Further Reading

There are a lot of resources available if you want to learn more about Pytorch vs Tensorflow. Here are a few that we recommend:

-Pytorch vs Tensorflow: A Comprehensive Comparison (

-Pytorch or TensorFlow: What’s the Difference? (

-TensorFlow vs PyTorch: Which should you use in 2021? (

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