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PyTorch VS Wasmer

Compare PyTorch VS Wasmer and see what are their differences

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PyTorch logo PyTorch

Open source deep learning platform that provides a seamless path from research prototyping to...

Wasmer logo Wasmer

The Universal WebAssembly Runtime
  • PyTorch Landing page
    Landing page //
    2023-07-15
  • Wasmer Landing page
    Landing page //
    2023-06-26

PyTorch features and specs

  • Dynamic Computation Graph
    PyTorch uses a dynamic computation graph, which allows for interactive and flexible model building. This is particularly beneficial for researchers who need to modify the network architecture on-the-fly.
  • Pythonic Nature
    PyTorch is designed to be deeply integrated with Python, making it very intuitive for Python developers. The framework feels more 'native' to Python, which improves the ease of learning and use.
  • Strong Community Support
    PyTorch has a large, active, and growing community. This means abundant resources such as tutorials, forums, and third-party tools are available to help developers solve problems and share solutions.
  • Flexibility and Control
    PyTorch offers granular control over computations and provides extensive debugging capabilities. This level of control is beneficial for tasks that require precise tuning and custom implementations.
  • Support for GPU Acceleration
    PyTorch offers seamless integration with GPU hardware, which significantly accelerates the computation process. This makes it highly efficient for deep learning tasks.
  • Rich Ecosystem
    PyTorch has a rich ecosystem including libraries like torchvision, torchaudio, and torchtext, which are specialized for different data types and can significantly shorten development times.

Possible disadvantages of PyTorch

  • Limited Production Deployment Tools
    PyTorch is primarily designed for research rather than production. While deployment tools like TorchServe exist, they are not as mature or integrated as solutions offered by other frameworks like TensorFlow.
  • Lesser Adoption in Industry
    While PyTorch is popular among researchers, it has historically seen less adoption in industry compared to TensorFlow, which means there might be fewer resources for large-scale production deployments.
  • Inconsistent API Changes
    As PyTorch continues to evolve rapidly, occasionally there are breaking changes or inconsistent API updates. This can create maintenance challenges for existing codebases.
  • Steeper Learning Curve for Beginners
    Despite its Pythonic design, PyTorch's focus on flexibility and control can make it slightly harder for beginners to get started compared to some other high-level libraries and frameworks.
  • Less Mature Documentation
    Although the documentation is improving, it has been historically less comprehensive and mature compared to other frameworks like TensorFlow, which can make it difficult to find detailed, clear information.

Wasmer features and specs

  • Cross-platform
    Wasmer enables running WebAssembly modules on various platforms like Linux, macOS, and Windows, enhancing portability and flexibility for developers.
  • Performance
    Wasmer is capable of near-native execution speeds, allowing applications to run efficiently by leveraging just-in-time (JIT) or ahead-of-time (AOT) compilation.
  • Language Agnostic
    Wasmer supports multiple programming languages, enabling developers to write in their preferred language and compile it to WebAssembly, enhancing inclusivity and ease of use.
  • Sandboxing
    With Wasmer, applications can run in a secure sandboxed environment, reducing potential security risks often associated with executing untrusted code.
  • Integration
    Wasmer can be embedded into different host languages like JavaScript, Rust, Python, etc., allowing seamless integration into existing projects and workflows.

Possible disadvantages of Wasmer

  • Limited Ecosystem
    Compared to more established technologies, the relatively newer ecosystem around Wasmer might result in fewer libraries, tools, and community support.
  • Complexity
    For developers unfamiliar with WebAssembly or looking for a simple solution, the setup and configuration of Wasmer might pose an initial learning curve.
  • Maturity of WebAssembly
    As WebAssembly is still evolving, some advanced features might not be fully supported, potentially affecting application development and deployment.
  • Debugging
    Debugging WebAssembly modules can be more challenging compared to more traditional binary formats or languages due to limited tooling and support.

PyTorch videos

+ Add

PyTorch in 5 Minutes

More videos:

  • Review - Jeremy Howard: Deep Learning Frameworks - TensorFlow, PyTorch, fast.ai | AI Podcast Clips
  • Review - PyTorch at Tesla - Andrej Karpathy, Tesla

Wasmer videos

+ Add

Syrus Akbary – Wasmer for web3 apps

More videos:

  • Review - My Thoughts on ChurnKit, FlowCV and WAPM!

Category Popularity

0-100% (relative to PyTorch and Wasmer)

PyTorch

Wasmer

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Software Development
0 0%
Software Development
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Developer Tools
0 0%
Developer Tools
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare PyTorch and Wasmer

PyTorch Reviews

10 Python Libraries for Computer Vision
Similar to TensorFlow and Keras, PyTorch and torchvision offer powerful tools for computer vision tasks. PyTorch’s dynamic computation graph and torchvision’s datasets and pre-trained models make it easy to implement tasks such as image classification, object detection, and style transfer.
Source: clouddevs.com
25 Python Frameworks to Master
Along with TensorFlow, PyTorch (developed by Facebook’s AI research group) is one of the most used tools for building deep learning models. It can be used for a variety of tasks such as computer vision, natural language processing, and generative models.
Source: kinsta.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
PyTorch is another open-source machine learning framework that is widely used in academia and industry. PyTorch provides excellent support for building deep learning models, and it has several pre-trained models for computer vision tasks, making it the ideal tool for several computer vision applications. PyTorch offers a user-friendly interface that makes it easier for...
Source: www.uubyte.com
PyTorch vs TensorFlow in 2022
When we compare HuggingFace model availability for PyTorch vs TensorFlow, the results are staggering. Below we see a chart of the total number of models available on HuggingFace that are either PyTorch or TensorFlow exclusive, or available for both frameworks. As we can see, the number of models available for use exclusively in PyTorch absolutely blows the competition out of...
Source: www.assemblyai.com
15 data science tools to consider using in 2021
First released publicly in 2017, PyTorch uses arraylike tensors to encode model inputs, outputs and parameters. Its tensors are similar to the multidimensional arrays supported by NumPy, another Python library for scientific computing, but PyTorch adds built-in support for running models on GPUs. NumPy arrays can be converted into tensors for processing in PyTorch, and vice...
Source: searchbusinessanalytics.techtarget.com

Wasmer Reviews

We have no reviews of Wasmer yet.
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Social recommendations and mentions

Based on our record, PyTorch should be more popular than Wasmer. It has been mentiond 132 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

PyTorch mentions (132)

  • Top Programming Languages for AI Development in 2025
    With the quick emergence of new frameworks, libraries, and tools, the area of artificial intelligence is always changing. Programming language selection. We're not only discussing current trends; we're also anticipating what AI will require in 2025 and beyond. - Source: dev.to / 7 days ago
  • Fine-tuning LLMs locally: A step-by-step guide
    Next, we define a training loop that uses our prepared data and optimizes the weights of the model. Here's an example using PyTorch:. - Source: dev.to / 27 days ago
  • 10 Must-Have AI Tools to Supercharge Your Software Development
    8. TensorFlow and PyTorch: These frameworks support AI and machine learning integrations, allowing developers to build and deploy intelligent models and workflows. TensorFlow is widely used for deep learning applications, offering pre-trained models and extensive documentation. PyTorch provides flexibility and ease of use, making it ideal for research and experimentation. Both frameworks support neural network... - Source: dev.to / 3 months ago
  • Automating Enhanced Due Diligence in Regulated Applications
    Frameworks like TensorFlow and PyTorch can help you build and train models for various tasks, such as risk scoring, anomaly detection, and pattern recognition. - Source: dev.to / 3 months ago
  • Must-Know 2025 Developer’s Roadmap and Key Programming Trends
    Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 3 months ago
View more

Wasmer mentions (52)

  • Hello world from a WASM module in a static binary
    I decided initially to use Wasmer and ended filing a question on their repository because their own native binary build command doesn't work as expected. - Source: dev.to / 2 months ago
  • WebAssembly: A promising technology that is quietly being enshitified
    I applaud the author on how clear he made the argument. Note: I work at Wasmer (https://wasmer.io), a WebAssembly runtime. - Source: Hacker News / 12 months ago
  • Bebop v3: a fast, modern replacement to Protocol Buffers
    This is awesome. I'd love to have upstream support in Wasmer ( https://wasmer.io ). - Source: Hacker News / about 1 year ago
  • Show HN: dockerc – Docker image to static executable "compiler"
    Unfortunately cosmopolitan wouldn't work for dockerc. Cosmopolitan works as long as you only use it but container runtimes require additional features. Also containers contain arbitrary executables so not sure how that would work either... As for WASM, this is already possible using container2wasm[0] and wasmer[1]'s ability to generate static binaries. [0]: https://github.com/ktock/container2wasm. - Source: Hacker News / about 1 year ago
  • Howto: WASM runtimes in Docker / Colima
    I could not find any guide how to add WASM container capability to Docker running on Colima. This guide provides a few Colima templates for exactly this, which adds WasmEdge, Wasmtime and Wasmer runtime types. - Source: dev.to / over 1 year ago
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What are some alternatives?

When comparing PyTorch and Wasmer, you can also consider the following products

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

Oh My Zsh - A delightful community-driven framework for managing your zsh configuration.

Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

tmux - tmux is a terminal multiplexer: it enables a number of terminals (or windows), each running a...

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

picocli - Application and Data, Languages & Frameworks, and Shell Utilities

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