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Codeium VS Keras

Compare Codeium VS Keras and see what are their differences

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Codeium logo Codeium

Free AI-powered code completion for *everyone*, *everywhere*

Keras logo Keras

Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
  • Codeium Landing page
    Landing page //
    2023-05-10
  • Keras Landing page
    Landing page //
    2023-10-16

Codeium features and specs

  • Free to Use
    Codeium is available for free, making it accessible to a wide range of users, including individuals and businesses with budget constraints.
  • Advanced AI Technology
    Utilizes state-of-the-art AI models to provide smart code completion, error checking, and other features that enhance developer productivity.
  • Multi-language Support
    Supports a variety of programming languages, making it versatile and useful for developers working in different stacks.
  • User-Friendly Interface
    Designed with a user-friendly interface that makes it easy for both beginners and experienced developers to navigate and use its features.
  • Robust Integration
    Can be integrated with popular code editors like Visual Studio Code, providing seamless usability within existing workflows.
  • Continuous Updates
    Regular updates ensure that the tool stays current with the latest programming standards and technologies.

Possible disadvantages of Codeium

  • Data Privacy Concerns
    Since the tool processes raw code, there may be concerns about data privacy and security for sensitive projects.
  • Limited Offline Functionality
    Requires an internet connection for full functionality, which can be a drawback for developers working in offline or remote environments.
  • Learning Curve
    Despite its user-friendly design, there can be a learning curve for new users to fully understand and utilize all the features.
  • Potential Over-reliance
    Developers might become overly reliant on automated code suggestions, which could impact their coding skills in the long term.
  • Variable Performance
    Performance may vary depending on the complexity of the codebase and the specific languages being used.
  • Integration Bugs
    Like any software, there could be occasional bugs or issues during integration with different development environments.

Keras features and specs

  • User-Friendly
    Keras provides a simple and intuitive interface, making it easy for beginners to start building and training models without needing extensive experience in deep learning.
  • Modularity
    Keras follows a modular design, allowing users to easily plug in different neural network components, such as layers, activation functions, and optimizers, to create complex models.
  • Pre-trained Models
    Keras includes a wide range of pre-trained models and offers easy integration with transfer learning techniques, reducing the time required to achieve good results on new tasks.
  • Integration with TensorFlow
    As part of TensorFlow’s ecosystem, Keras provides deep integration with TensorFlow functionalities, enabling users to leverage TensorFlow's powerful features and performance optimizations.
  • Extensive Documentation
    Keras has comprehensive and well-organized documentation, along with numerous tutorials and code examples, making it easier for developers to learn and use the framework.
  • Community Support
    Keras benefits from a large and active community, which provides support through forums, GitHub, and specialized user groups, facilitating the resolution of issues and sharing of best practices.

Possible disadvantages of Keras

  • Performance Limitations
    Due to its high-level abstraction, Keras may incur performance overheads, making it less suitable for scenarios requiring extremely fast execution and low-level optimizations.
  • Limited Low-Level Control
    The simplicity and abstraction of Keras can be a downside for advanced users who need fine-grained control over model components and custom operations, which may require them to resort to lower-level frameworks.
  • Scalability Issues
    In some complex applications and large-scale deployments, Keras might face scalability challenges, where more specialized or low-level frameworks could handle such tasks more efficiently.
  • Dependency on TensorFlow
    While the integration with TensorFlow is generally an advantage, it also means that the performance and features of Keras are closely tied to the development and updates of TensorFlow.
  • Lagging Behind Latest Research
    Keras, being a user-friendly high-level API, might not always incorporate the latest cutting-edge research advancements in deep learning as quickly as more research-oriented frameworks.

Codeium videos

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Codeium: Free Copilot Alternative

Keras videos

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3. Deep Learning Tutorial (Tensorflow2.0, Keras & Python) - Movie Review Classification

More videos:

  • Review - Movie Review Classifier in Keras | Deep Learning | Binary Classifier
  • Review - EKOR KERAS!! Review and Bike Check DARTMOOR HORNET 2018 // MTB Indonesia

Category Popularity

0-100% (relative to Codeium and Keras)

Codeium

Keras

AI
100 100%
AI
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Developer Tools
100 100%
Developer Tools
0% 0
Data Science Tools
0 0%
Data Science 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 Codeium and Keras

Codeium Reviews

10 Best Github Copilot Alternatives in 2024
Yes, some free alternatives to GitHub Copilot like Codeium offer features that can be suitable for enterprise use. However, for advanced needs, you might consider paid options like TabNine Enterprise or DeepCode (Snyk Code), which provide additional support and security features.
Source: www.geeksforgeeks.org
The Best GitHub Copilot Alternatives for Developers
Another notable feature of Codeium is context pinning. It allows developers to pin any scope of code, such as a repository, a file, or a function, so Codeium takes the code in that section more seriously when generating responses. Developers can apply this feature once and save it while they work, enhancing accuracy in coding tasks. Codeium is capable of meeting a variety of...
Source: softteco.com
6 GitHub Copilot Alternatives You Should Know
Codeium is another LLM-driven coding assistant designed to enhance productivity and code quality for developers. It provides smart code completions and refactorings. Codeium supports a variety of programming languages and integrates with popular IDEs.
Source: swimm.io

Keras Reviews

10 Python Libraries for Computer Vision
TensorFlow and Keras are widely used libraries for machine learning, but they also offer excellent support for computer vision tasks. TensorFlow provides pre-trained models like Inception and ResNet for image classification, while Keras simplifies the process of building, training, and evaluating deep learning models.
Source: clouddevs.com
25 Python Frameworks to Master
Keras is a high-level deep-learning framework capable of running on top of TensorFlow, Theano, and CNTK. It was developed by François Chollet in 2015 and is designed to provide a simple and user-friendly interface for building and training deep learning models.
Source: kinsta.com
15 data science tools to consider using in 2021
Keras is a programming interface that enables data scientists to more easily access and use the TensorFlow machine learning platform. It's an open source deep learning API and framework written in Python that runs on top of TensorFlow and is now integrated into that platform. Keras previously supported multiple back ends but was tied exclusively to TensorFlow starting with...
Source: searchbusinessanalytics.techtarget.com

Social recommendations and mentions

Codeium might be a bit more popular than Keras. We know about 44 links to it since March 2021 and only 35 links to Keras. 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.

Codeium mentions (44)

  • 15 AI tools that almost replace a full dev team but please don’t fire us yet
    Codeium: Supports multiple editors and privacy-conscious teams. - Source: dev.to / 15 days ago
  • Building a narrative game with Next.js and AI
    The only workflow change was switching IDEs, from VSCode/Copilot to Windsurf/Cascade, as it was depicted as a more performant AI regarding the app context. - Source: dev.to / about 2 months ago
  • Vibe coding a nifty Umbraco tool
    What started as a slow Friday turned into a productive coding session using Windsurf, Codeiums AI-powered IDE, to create a block thumbnail generator for Umbraco block editors. - Source: dev.to / 2 months ago
  • Best AI Code Editors in 2025
    Built on VS Code (sensing a theme here?), Windsurf offers a sophisticated AI-powered development environment with its Supercomplete and Cascade features. Developed by Codeium, it focuses on real-time workspace understanding and intelligent code assistance. - Source: dev.to / 3 months ago
  • AI Revolution for Developers not just corporates
    Windsurf: Generates contextually relevant code based on developer's code accelerating development. - Source: dev.to / 3 months ago
View more

Keras mentions (35)

  • Top Programming Languages for AI Development in 2025
    The unchallenged leader in AI development is still Python. And Keras, and robust community support. - Source: dev.to / 19 days ago
  • Top 8 OpenSource Tools for AI Startups
    If you need simplicity, Keras is a great high-level API built on top of TensorFlow. It lets you quickly prototype neural networks without worrying about low-level implementations. Keras is perfect for getting those first models up and running—an essential part of the startup hustle. - Source: dev.to / 7 months ago
  • Top 5 Production-Ready Open Source AI Libraries for Engineering Teams
    At its heart is TensorFlow Core, which provides low-level APIs for building custom models and performing computations using tensors (multi-dimensional arrays). It has a high-level API, Keras, which simplifies the process of building machine learning models. It also has a large community, where you can share ideas, contribute, and get help if you are stuck. - Source: dev.to / 8 months ago
  • Using Google Magika to build an AI-powered file type detector
    The core model architecture for Magika was implemented using Keras, a popular open source deep learning framework that enables Google researchers to experiment quickly with new models. - Source: dev.to / 11 months ago
  • My Favorite DevTools to Build AI/ML Applications!
    As a beginner, I was looking for something simple and flexible for developing deep learning models and that is when I found Keras. Many AI/ML professionals appreciate Keras for its simplicity and efficiency in prototyping and developing deep learning models, making it a preferred choice, especially for beginners and for projects requiring rapid development. - Source: dev.to / about 1 year ago
View more

What are some alternatives?

When comparing Codeium and Keras, you can also consider the following products

GitHub Copilot - Your AI pair programmer. With GitHub Copilot, get suggestions for whole lines or entire functions right inside your editor.

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.

Tabnine - TabNine is the all-language autocompleter. We use deep learning to help you write code faster.

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

Glambase - The Glambase platform provides the ability and the tools to create, promote, and monetize AI-powered virtual influencers.

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

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