neptune.ai vs Weights & Biases

by Gralio Mar 11, 2025

Neptune.ai and Weights & Biases are both powerful tools for machine learning model development. Neptune.ai prioritizes detailed experiment tracking and management, while Weights & Biases emphasizes collaboration and streamlined workflows. The choice depends on whether detailed logging or rapid iteration and deep learning framework integration is more critical for your team.

At Gralio.ai we help to simplify your decision-making process by offering detailed, side-by-side software comparisons like this one, to help you confidently choose the tool that aligns with your business goals.

This comparison was created by analysing 81 reviews and 60 websites, saving 57 minutes of reading.

neptune.ai

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Weights & Biases

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About

Neptune.ai is a software tool that helps teams track and manage their machine learning experiments. It provides a centralized platform to log, organize, and visualize model training data, making it easier to identify and compare the performance of different models. Neptune.ai focuses on scalability and accuracy for large-scale machine learning projects, offering real-time monitoring and seamless integration with popular machine learning tools. This helps teams save time, make better decisions, and improve the efficiency of their model development process.

Weights & Biases is a tool that helps teams build machine learning models more efficiently. It allows users to track their model's performance, compare different model variations, and easily share results with colleagues. This helps streamline the model development process and leads to faster iteration and improvement.

Summary

Main difference

Neptune.ai offers a robust, scalable platform with a focus on experiment tracking and model management for machine learning projects, ideal for teams prioritizing detailed logging and comparison. Weights & Biases excels in collaborative model building and streamlined workflows, particularly suited for teams focused on rapid iteration and development using PyTorch and TensorFlow.

Relative strengths of neptune.ai (compared to Weights & Biases)

Stronger focus on experiment tracking and model comparison.
Scalable architecture suitable for large-scale projects.
More affordable pricing for teams, especially with the free tier for individuals and commercial use.

Relative weaknesses of neptune.ai (compared to Weights & Biases)

Less comprehensive integrations with deep learning frameworks compared to Weights & Biases.
Limited advanced features for hyperparameter tuning and model optimization.
Simpler reporting and dashboarding capabilities.

What companies are using neptune.ai and Weights & Biases?

No data

Who should use neptune.ai VS. Weights & Biases

Neptune.ai is a user-friendly platform ideal for data scientists and machine learning engineers managing large-scale projects. It simplifies experiment tracking, model comparison, and progress monitoring. Users appreciate its intuitive interface, robust integrations, and excellent customer support. While some users desire enhanced search and schema versioning, its ease of use and helpful support make it a valuable tool for streamlining the model development process.

Weights & Biases helps machine learning teams track model performance, compare variations, and share results. Users praise its intuitive API and integration with PyTorch and TensorFlow. However, some dislike the unclear cache management and pricing based on tracked hours. It's highly rated (4.6/5 on G2).

Ideal for teams of all sizes, from individual users to large enterprises.
Suitable for any industry leveraging machine learning for large-scale projects.

Best for medium to large businesses (100+ employees).
Ideal for machine learning teams, especially in software and IT.

neptune.ai and Weights & Biases features

Supported

Partially supported

Not supported

Type in the name of the feature or in your own words tell us what you need

AI Application Development

Not supported

Neptune.ai does not seem to support the requested features.

Supported

Weights & Biases supports streamlined AI application development, including LLM call and document retrieval monitoring.
AI Model Building and Management

Supported

Neptune supports building and managing AI models, including tracking training parameters and logging key metrics.

Supported

Weights & Biases tracks model training parameters like epochs and learning rates, and logs key metrics.
Report Generation

Supported

Neptune supports customizable reports with multi-run comparisons and sharing options.

Supported

Reports compile experimental results, metrics, and data.
Interactive dashboards

Supported

Neptune.ai enables building interactive dashboards for comparing ML experiments.

Supported

Weights & Biases allows users to create interactive dashboards for data exploration and result visualization.
MATLAB integration

Not supported

Neptune.ai does not appear to have direct MATLAB integration.

Supported

Weights & Biases integrates with MATLAB.
Model parallelism

Partially supported

Model parallelism is supported indirectly via integrations with frameworks like PyTorch.

Not supported

Model parallelism is not directly supported.

Qualities

Value and Pricing Transparency

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Customer Service

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Ease of Use

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Reliability and Performance

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Ease of Implementation

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Scalability

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neptune.ai and Weights & Biases Pricing

Neptune.ai offers simple pricing for a scalable experiment tracker with different plans for individual users, teams, and enterprises. They offer a free plan for personal and commercial use and a free license for students, professors, researchers, and Kaggle competition participants. All plans come with unlimited logging hours. For organizations with unique security requirements, Neptune.ai offers a self-hosted plan that can be deployed on the user's infrastructure or private cloud.

Plans

See full Pricing page

No data

We couldn't find a pricing page for Weights & Biases.

neptune.ai and Weights & Biases review insights

Users love

Highly praised for its ease of use and integration with various ML frameworks.
Intuitive user interface and excellent customer support.
Effective for tracking experiment performance and progress, aiding in decision-making.
Helpful for team collaboration and project overview.
Offers both cloud-based and self-hosted options, with the latter providing advantages like unlimited storage.

Intuitive and easy-to-use API for tracking model performance and experiments.
Seamless integration with popular machine learning frameworks like PyTorch and TensorFlow.
Comprehensive performance visualization tools that eliminate the need for manual plotting and tracking.
Excellent collaboration features, allowing teams to easily share results and insights.
Robust experiment tracking capabilities, enabling users to compare different model variations and hyperparameters effectively.

Users dislike

Limited data monitoring and model versioning capabilities, though these are reportedly in development.
Search functionality could be improved for projects with numerous experiments.
Flexibility in tracked data schema can lead to inconsistencies and lacks version control.
Limited advanced plotting features, although this is said to be under development.
Some users desire stricter schema versioning and typing options.

Occasional issues with zombie processes that can terminate other training runs upon killing them.
Unclear cache management system, making it difficult to clean up old logs.
Limited team functionality in the free version.
The pricing model based on "tracked hours" can be expensive for users with multiple GPUs or large-scale experiments.
Some UI elements, such as the Runs data table, can be slow and laggy.
Graphs lack intuitive zoom functionality, making navigation within zoomed-in views difficult.

neptune.ai and Weights & Biases Ratings

G2

4.8/5

(49)

G2

4.6/5

(32)
Glassdoor

4.3/5

(72)

Company health

Employee growth

5% increase in the last year

14% increase in the last year

Web traffic

5% increase in the last quarter

11% decrease in the last quarter

Financing

January 2022 - $13M

May 2023 - $250M

How do Neptune.ai and Weights & Biases compare in managing large datasets?

Neither product description explicitly mentions features specifically designed for managing large datasets, though both are geared towards machine learning experimentation which often involves such data. More information is needed to determine how each platform handles storage, processing, and versioning of large datasets. Neptune.ai users mention "unlimited storage" with the self-hosted option, which could be advantageous for large datasets. However, there's no information about Weights & Biases' data handling capacity for large datasets within the provided texts.

Which product offers better visualization tools for comparing model variations?

Weights & Biases offers better visualization tools for comparing model variations. Both products offer interactive dashboards, but Weights & Biases is praised for its comprehensive performance visualization tools, eliminating manual plotting and enabling effective comparison of different model variations and hyperparameters. While Neptune.ai offers scatter plots, user reviews mention its limited advanced plotting features. Therefore, for the specific need of comparing model variations visually, Weights & Biases appears to be the stronger choice.

What are the advantages of neptune.ai?

Neptune.ai offers a more transparent and positive pricing structure, including a free tier for personal and commercial use, unlike Weights & Biases, which has a less clear and negatively perceived pricing model. Neptune.ai also receives praise for its ease of use and excellent customer support. Furthermore, users appreciate Neptune.ai's flexibility with self-hosted options for enhanced data security and unlimited storage, which addresses some limitations of Weights & Biases regarding cost for large-scale experiments.

What are the disadvantages of neptune.ai?

Neptune.ai has some limitations regarding data monitoring and model versioning capabilities. The search functionality could be improved for larger projects, and the flexible data schema, while useful, lacks version control and can lead to inconsistencies. Some users also desire more advanced plotting features and stricter schema typing.

Alternatives to neptune.ai and Weights & Biases

TensorFlow

TensorFlow is a free and open-source software platform designed to help you build, launch, and manage machine learning applications. It offers a set of tools and resources that simplify the process of developing and training machine learning models, making it possible to apply these powerful technologies to various tasks such as image recognition, natural language processing, and predictive modeling. TensorFlow can be used in different environments, including web browsers, mobile devices, and large-scale cloud computing systems.

Qlik AutoML

Qlik AutoML helps you make predictions from your company's data without needing a data scientist. It automatically analyzes your data, builds models, and explains the results in an easy-to-use interface. Qlik AutoML is part of Qlik's suite of data analytics tools that help businesses uncover insights for better decision-making.

Carbon

Carbon is a software tool that helps businesses connect their data to Large Language Models (LLMs). This means LLMs can better understand and utilize your company's information. Carbon allows access to data from various sources like Dropbox and Google Drive, making it easier to find specific information within your company's data. Carbon is designed to be easy for developers to use and can be integrated into existing applications or websites.

ClearML

ClearML is an open-source platform designed to simplify and accelerate the development and deployment of AI models. It offers tools for managing data, tracking experiments, automating workflows, and deploying models. This comprehensive platform caters to different user roles within a company, providing a centralized hub for collaboration and efficient resource utilization, regardless of the complexity of your AI projects. ClearML aims to streamline the entire AI lifecycle, making it faster and easier for businesses to implement AI solutions.

SAS Model Manager

SAS Model Manager is a software tool designed to help businesses manage their AI models. It lets you track model performance, ensure they are working correctly, and easily deploy them for use across your business. With its automation features, you can streamline your model management processes, making it easier for your teams to maintain and monitor model performance over time.

DAGsHub

DAGsHub is a platform designed specifically for data science teams to manage their work. It provides tools for tracking experiments, managing data, and collaborating on machine learning projects. DAGsHub helps teams organize their projects, track progress, and improve the reliability of their models. It integrates with popular data science tools like Git and MLflow, offering a centralized hub for all machine learning project needs.

Page co-authored by

Michal Kaczor

CEO at Gralio

Michal has worked at startups for many years and writes about topics relating to software selection and IT management. As a former consultant for Bain, a business advisory company, he also knows how to understand needs of any business and find solutions to its problems.

Tymon Terlikiewicz

CTO at Gralio

Tymon is a seasoned CTO who loves finding the perfect tools for any task. He recently headed up the tech department at Batmaid, a well-known Swiss company, where he managed about 60 software purchases, including CX, HR, Payroll, Marketing automation and various developer tools.

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