---
title: Weights & Biases Reviews
meta_title: 'Weights & Biases Reviews 2026: Details, Pricing, & Features | G2'
meta_description: Filter 63 reviews by the users' company size, role or industry to
  find out how Weights & Biases works for a business like yours.
aggregate_rating:
  rating_value: 4.5
  review_count: 63
  scale: '5'
date_modified: '2026-10-01'
parent_category:
  name: Artificial Intelligence
  url: https://www.g2.com/categories/artificial-intelligence
---


# Weights & Biases Reviews
**Vendor:** CoreWeave  
**Category:** [MLOps Platforms](https://www.g2.com/categories/mlops-platforms)  
**Average Rating:** 4.5/5.0  
**Total Reviews:** 63  
**AI Verified:** At least 10 G2 reviewers have confirmed using this product's AI features and functionality.
## About Weights & Biases
Weights & Biases is the AI developer platform to build AI applications and models with confidence. ML engineers and AI developers use W&B Weave and W&B Models to coordinate all LLMops and MLops processes, including evaluating, debugging, training, fine-tuning, and deploying. W&B Weave helps developers evaluate, monitor and iterate on their AI applications to continuously improve quality, latency, cost, and safety. W&B Models boosts experiment speed and team collaboration among ML teams, helping them bring models to production faster while ensuring performance, data reliability, and security. W&B also serves as the system of record for all ML and AI activities.



## Weights & Biases Pros & Cons
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.

**What users like:**

- Users value the **ease of use** in Weights & Biases, enjoying seamless tracking and sharing of training runs. (3 reviews)
- Users appreciate the **seamless integration and ease of use** of Weights & Biases, enhancing their research and teaching experiences. (2 reviews)
- Users appreciate the **setup ease** of Weights & Biases, enabling effortless integration and quick result management. (2 reviews)
- Users commend the **responsive and knowledgeable customer support** of Weights & Biases, enhancing their overall experience. (1 reviews)
- Users appreciate the **customization flexibility** of Weights & Biases, enabling tailored logging and insightful model comparisons. (1 reviews)
- Users love the **simplicity and efficiency of data visualization** in Weights & Biases, streamlining their analytical processes. (1 reviews)
- Users appreciate the **easy integrations** with libraries like PyTorch Lightning, enhancing workflow and productivity. (1 reviews)
- Implementation Ease (1 reviews)
- Integrations (1 reviews)
- Users love the **seamless integration** of Weights & Biases with popular ML libraries, enhancing workflow and productivity. (1 reviews)

**What users dislike:**

- Users find the **limited documentation on basic functionality** of Weights & Biases frustrating and unhelpful. (1 reviews)
- Users find the **lack of guidance** frustrating when seeking basic functionalities due to inadequate documentation in W&B. (1 reviews)
- Users highlight the **lack of tools** for effectively managing and discarding non-useful runs in Weights & Biases. (1 reviews)
- Users desire more flexibility with **missing features** like global normalization and better window management upon reload. (1 reviews)
- Users find the **poor documentation** of Weights & Biases frustrating when seeking basic functionalities. (1 reviews)
- Users experience **slow performance** due to laggy servers and finicky UI elements, impacting their overall experience. (1 reviews)
- User Accessibility (1 reviews)

## Weights & Biases Reviews
  ### 1. Effortless W&B Integration with Powerful Remote Monitoring and Visualizations

**Rating:** 4.5/5.0 stars

**Reviewed by:** Nitin g. | Student, Small-Business (50 or fewer emp.)

**Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user.

**Validated Reviewer:** Validated through LinkedIn

**Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review.

**Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review.

**Reviewed Date:** September 26, 2026

**What do you like best about Weights & Biases?**

The integration simplicity is by far the biggest highlight. Dropping wandb.init() and wandb.log() into an existing training loop takes less than two minutes and immediately starts streaming loss curves and custom validation metrics. Being able to visualize parallel coordinates plots during hyperparameter sweeps makes spotting optimal learning rates and weight decays much faster than digging through scattered local logs. The hosted dashboard also means I can monitor long-running training runs remotely without keeping an active SSH session alive.

**What do you dislike about Weights & Biases?**

When running long experiments with high-frequency logging or heavy visual artifacts, the browser dashboard can feel somewhat sluggish to render and filter through dozens of runs. Also, if there is a brief network drop during a script execution, the offline queue occasionally takes an extra push to sync up cleanly with the cloud project, which can be confusing until you manually verify the run status via CLI.

**What problems is Weights & Biases solving and how is that benefiting you?**

Before using W&B, keeping track of different training iterations, random seeds, and checkpoint weights meant dealing with cluttered local TensorBoard directories and manually parsed CSV files. Weights & Biases centralizes every run configuration, metric curve, and code commit hash in a single organized workspace. This completely removes the guesswork about which hyperparameter setup gave the best validation score, saving roughly 30% of my time during model evaluation cycles.

  ### 2. Weights & Biases Makes Experiment Tracking and Model Comparison Effortless

**Rating:** 4.5/5.0 stars

**Reviewed by:** Shubham S. | Co-Founder, Small-Business (50 or fewer emp.)

**Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user.

**Validated Reviewer:** Validated through a business email account

**Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review.

**Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review.

**Reviewed Date:** September 09, 2026

**What do you like best about Weights & Biases?**

What I like best about Weights & Biases is how it makes it easier to track experiments and understand how different model versions are performing. The dashboards are useful for comparing runs, metrics, and results, and having everything organized in one place makes the development process much easier to manage. It is especially helpful when working on multiple experiments at the same time.

**What do you dislike about Weights & Biases?**

The main thing I dislike is that it can feel a bit overwhelming when you first start using it. There are a lot of metrics and configuration options, so it takes some time to figure out which ones are actually useful for your workflow. Once set up, though, it becomes much easier to work with.

**What problems is Weights & Biases solving and how is that benefiting you?**

Weights & Biases helps keep ML experiments organized by tracking runs, metrics, model versions, and results in one place. It makes it easier to compare experiments, understand what is improving or getting worse, and reproduce successful results. This saves time when working on multiple models and reduces the need to track everything manually.

  ### 3. Seamless ML Experiment Tracking with a Clean UI and Effortless Integrations

**Rating:** 4.5/5.0 stars

**Reviewed by:** Anson T. | Owner/Operator/CEO, Small-Business (50 or fewer emp.)

**Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user.

**Validated Reviewer:** This review contains authentic analysis and has been reviewed by our team

**Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review.

**Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review.

**Reviewed Date:** August 25, 2026

**What do you like best about Weights & Biases?**

What stands out most about Weights & Biases is how seamlessly it tracks ML experiments through a clean, intuitive UI/UX. It integrates effortlessly with frameworks like PyTorch and Hugging Face, which makes real-time performance monitoring and fast, reliable data logging feel almost automatic. Onboarding is quick and well supported by strong documentation, so it’s easy to get up and running without friction. The AI intelligence features also help keep artifact management organized and make hyperparameter evaluation straightforward, which contributes to a fantastic overall ROI.

**What do you dislike about Weights & Biases?**

The main drawback of Weights & Biases is that data and storage costs can ramp up quickly when you’re logging very large runs, high-resolution artifacts, or big media files. Also, although the UI is packed with features, the sheer number of metrics and customizable panels can feel overwhelming at first and lead to a steep learning curve for new team members during onboarding.

**What problems is Weights & Biases solving and how is that benefiting you?**

Weights & Biases addresses the problem of fragmented machine learning workflows by offering a centralized platform to track experiments, version models, and visualize metrics in one place. It removes the need for manual logging and for keeping results scattered across notebooks. For me, this saves a lot of time during model evaluation, makes it much easier to debug hyperparameter performance, and helps ensure full reproducibility across complex training runs.

  ### 4. Effortless MLOps and Experiment Tracking with Powerful Real-Time Dashboards

**Rating:** 4.5/5.0 stars

**Reviewed by:** Arpit C. | Computer Software Engineer, Computer Software, Small-Business (50 or fewer emp.)

**Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user.

**Validated Reviewer:** Validated through LinkedIn

**Source: Organic:** Organic review. This review was written entirely without invitation or incentive from G2, a seller, or an affiliate.

**Reviewed Date:** August 23, 2026

**What do you like best about Weights & Biases?**

Weights & Biases makes MLOps and experiment tracking feel effortless, with only minimal code required to get started (wandb.init()). Its real-time, interactive dashboards deliver immediate and detailed visualizations of training loss curves, the impact of hyperparameters, and system resource utilization (GPU/CPU). On top of that, robust artifact versioning and seamless integrations with frameworks like PyTorch, Hugging Face, and TensorFlow make model reproducibility and team-wide collaboration especially smooth. Our experience with Weights & Biases’ automated features has been outstanding, particularly in reducing manual trial-and-error during model training. Features like automated hyperparameter sweeps, background system metric logging, and threshold-based alerts remove the operational friction of running large-scale ML jobs. Instead of constantly monitoring training runs, we rely on automated early-stopping rules and webhook notifications to keep our pipeline efficient.

**What do you dislike about Weights & Biases?**

While W&B handles standard metric logging smoothly, the web console can suffer from noticeable UI latency when you load projects with hundreds of concurrent runs or with dense media artifacts. On top of that, keeping the workspace tidy can be a bit of a slog—for example, filtering and bulk-deleting failed experimental runs feels tedious. Finally, per-user pricing can scale steeply as you move from a small team workspace to an enterprise-wide deployment.

**What problems is Weights & Biases solving and how is that benefiting you?**

Before implementing Weights & Biases, we struggled with fragmented experiment tracking split between local TensorBoard logs and spreadsheet records. That setup made it hard for our engineering team to compare hyperparameter variations consistently and to reproduce model results.

Weights & Biases addressed this by giving us a unified, real-time dashboard with automated logging for loss curves, system metrics, hyperparameter sweeps, and model artifacts. We can now quickly compare dozens of concurrent training runs, set up automated early stopping for underperforming models, and keep strict version control over dataset-to-model lineage. As a result, we’ve cut down on wasted cloud GPU compute and significantly sped up our iteration cycle from model development through production deployment.

  ### 5. Essential ML Experiment Tracking with Real-Time Metrics and Team Collaboration

**Rating:** 4.5/5.0 stars

**Reviewed by:** Muhammed A. | Technical Project Manager , Logistics and Supply Chain, Small-Business (50 or fewer emp.)

**Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user.

**Validated Reviewer:** Validated through LinkedIn

**Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review.

**Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review.

**G2 Icon:** Our network of Icons are G2 members who are recognized for their outstanding contributions and commitment to helping others through their expertise.

**Reviewed Date:** July 31, 2026

**What do you like best about Weights & Biases?**

Weights & Biases has become an essential platform for managing machine learning experiments, model training, and performance tracking. The interface makes it easy to compare runs, visualize metrics in real time, and collaborate across teams, while integrations with popular ML frameworks simplify adoption. Experiment tracking, artifact versioning, and reproducibility features significantly reduce manual work, helping teams iterate faster, improve model quality, and maintain organized AI development workflows.

**What do you dislike about Weights & Biases?**

Weights & Biases offers a comprehensive feature set, but new users may face a learning curve when configuring advanced experiment tracking, reports, and team workflows. Large projects with thousands of experiment runs can sometimes make dashboards feel cluttered, and premium features may be costly for smaller teams. I would also like to see more customization options for visualizations and reporting, along with additional native integrations for enterprise MLOps environments.

**What problems is Weights & Biases solving and how is that benefiting you?**

Before using Weights & Biases, tracking machine learning experiments, comparing model performance, and managing training artifacts across multiple projects was time-consuming and difficult to reproduce. The platform centralized experiment tracking, visualization, model versioning, and collaboration in a single workspace, making it much easier to monitor progress and identify the best-performing models. This has reduced manual effort, improved reproducibility, accelerated model development cycles, and enabled the team to make faster, data-driven decisions throughout the ML lifecycle.

  ### 6. A Reliable Platform for Tracking Machine Learning Experiments

**Rating:** 4.0/5.0 stars

**Reviewed by:** Muhammad O. | Salesforce Business Analyst, Information Technology and Services, Small-Business (50 or fewer emp.)

**Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user.

**Validated Reviewer:** Validated through LinkedIn

**Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review.

**Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review.

**G2 Icon:** Our network of Icons are G2 members who are recognized for their outstanding contributions and commitment to helping others through their expertise.

**Reviewed Date:** July 25, 2026

**What do you like best about Weights & Biases?**

What I like most is how easy it is to get started and keep all my experiments organized in one place. The dashboard feels clean and intuitive, so it’s straightforward to track runs, compare results, and share progress with teammates. Overall, it helps me manage model development in a more structured way without ever feeling overly complicated.

**What do you dislike about Weights & Biases?**

The platform offers a lot of features, so it can feel a bit overwhelming when you’re first getting started. It took me some time to figure out where everything was and how it all fit together, but after I spent a little time exploring, it became much easier to navigate.

**What problems is Weights & Biases solving and how is that benefiting you?**

Weights & Biases helps me keep machine learning experiments organized by tracking runs, comparing results, and making it easier to see which changes actually improve a model. It saves time, supports collaboration, and makes it much simpler to reproduce past experiments rather than having to start from scratch.

  ### 7. Streamlined AI Debugging with Room for Improvement

**Rating:** 4.0/5.0 stars

**Reviewed by:** Vikash K. | SWE, Insurance, Mid-Market (51-1000 emp.)

**Validated Reviewer:** Validated through a business email account

**Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review.

**Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review.

**Reviewed Date:** September 16, 2026

**What do you like best about Weights & Biases?**

I like how easy it is to set up Weights & Biases for our insurance claims project. I can just integrate it into my Python code, and it automatically tracks our API costs and AI responses for the adjusters. I appreciate that it integrates perfectly with our FastAPI framework by simply adding a decorator. It is incredibly helpful to trace our project's execution without massive logging. Also, the evaluation tools are great, letting me test new prompts to improve how we extract policy data.

**What do you dislike about Weights & Biases?**

Setting up the automatic grading using LLM as a judge took a few days, which was a bit of a learning curve. The W&B dashboard has many older features for traditional machine learning, which our team doesn't use since we're focused on generative AI. This results in a crowded interface with extra menus, making it a bit overwhelming. I would prefer if each feature had its own screen, especially for GenAI tasks. It would also be helpful if the dashboard allowed for more customization to focus on specific tasks like LLM prompt testing and RAG observability. That would make it much more streamlined for our needs.

**What problems is Weights & Biases solving and how is that benefiting you?**

Weights & Biases fixes the black box problem in AI. When the AI gives a wrong policy code to an adjuster, Weights & Biases allows me to open a log and see exactly why that mistake happened. It shows me exactly which document chunks were retrieved, saving me hours of debugging time.

  ### 8. Weights & Biases Makes Experiment Tracking and Run Comparisons Effortless

**Rating:** 4.0/5.0 stars

**Reviewed by:** Anson D. | Software QA, Mid-Market (51-1000 emp.)

**Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user.

**Validated Reviewer:** Validated through a business email account

**Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review.

**Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review.

**Reviewed Date:** July 11, 2026

**What do you like best about Weights & Biases?**

What I like most about Weights & Biases is how easy it is to keep track of experiments in one place. The dashboard is well organized and makes it simple to compare runs, monitor metrics, and visualize results. It saves a lot of time compared to manually recording experiment details.

**What do you dislike about Weights & Biases?**

The platform has a lot of features, so it can feel a bit overwhelming when you're getting started. It took me some time to understand where everything was. Apart from that, I haven't faced any major issues while using it.

**What problems is Weights & Biases solving and how is that benefiting you?**

Weights & Biases helps me organize and track machine learning experiments instead of managing everything manually. Having metrics, logs, and experiment history in one dashboard makes it much easier to compare results and understand what changes are improving the model. It has made my workflow more organized and efficient.

  ### 9. Weights & Biases Review: The Ultimate Machine Learning Experiment Tracker & Collaboration Hub

**Rating:** 4.0/5.0 stars

**Reviewed by:** Ian d. | Head of AI and Computer Vision, Small-Business (50 or fewer emp.)

**Validated Reviewer:** Validated through a business email account

**Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review.

**Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review.

**Reviewed Date:** August 28, 2026

**What do you like best about Weights & Biases?**

Seamless, minimal-code integration: Getting started takes only 2–3 lines of Python (for example, wandb.init() and wandb.log()). It plugs in smoothly with major frameworks like PyTorch, TensorFlow, Hugging Face, XGBoost, and Ray, without pushing you into custom abstractions.

Centralized experimentation and live dashboards: Rather than juggling messy spreadsheets or scattered log files, W&B automatically captures metrics, system stats (GPU/CPU usage and memory), hyperparameters, git commits, and command-line arguments, and surfaces them in clean, interactive, real-time dashboards.

Artifact tracking and lineage: W&B Artifacts makes it straightforward to version datasets, models, and intermediate pipeline steps. Being able to tie a specific model checkpoint to the exact data version and code commit used to produce it helps ensure full reproducibility.

Collaborative reports: W&B Reports let you publish interactive, dynamic documents that combine live charts, rich Markdown text, and model evaluations. This makes it easier to share progress with teammates or stakeholders without relying on static screenshots.

Scalable model registry and sweeps: Setting up hyperparameter optimization with wandb.sweeps is simple, with support for Bayesian optimization and early-stopping strategies at scale across distributed GPU clusters.

**What do you dislike about Weights & Biases?**

High Cost at Scale: The free individual tier is quite generous, but team and enterprise pricing can ramp up quickly depending on user seats and hosted artifact storage. For large production teams generating heavy run volumes or storing multi-gigabyte model artifacts, costs can become prohibitive, especially when compared with open-source alternatives.

Storage and Bandwidth Overhead: Keeping large artifacts (datasets, large model checkpoints, image/audio logs) in the W&B cloud can consume substantial network bandwidth. If logging frequency isn’t tuned carefully, it can also slow down training jobs. On top of that, staying within cloud storage retention limits takes ongoing, hands-on maintenance.

Proprietary Vendor Lock-in: Unlike fully open-source options such as MLflow, W&B’s core backend is proprietary. If you decide to switch platforms, migrating historical experiment data, run logs, or custom dashboards can be difficult and time-consuming.

Steep Learning Curve for Advanced Features: Basic logging with wandb.log() is straightforward, but more complex workflows—like distributed sweeps across multi-node clusters, programmatic artifact lineage, or custom dynamic reporting—often require working through dense documentation and intricate configuration.

Self-Hosting Complexity: Deploying W&B Server (on-premises or in a private cloud VPC) to meet strict enterprise compliance or privacy requirements adds significant DevOps overhead. It typically involves Docker/Kubernetes management and licensing setup, and it’s far more involved than running a lightweight local server.

**What problems is Weights & Biases solving and how is that benefiting you?**

Weights & Biases solves the core challenges of machine learning chaos—such as fragmented experiment tracking in spreadsheets, lost model checkpoints, poor data lineage, and silent training failures—by centralizing hyperparameter logging, dataset versioning, and real-time GPU/system monitoring into an interactive dashboard. This benefits me by eliminating the guesswork of identifying which code and data produced a specific model, saving massive amounts of time and compute resources through instant failure detection, and making my entire development workflow fully reproducible and effortlessly collaborative.

  ### 10. Easy Experiment Tracking and Smooth PyTorch Lightning Integration

**Rating:** 4.5/5.0 stars

**Reviewed by:** Kumar S. | Research Intern in Natural Language Processing, Mid-Market (51-1000 emp.)

**Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user.

**Validated Reviewer:** Validated through LinkedIn

**Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review.

**Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review.

**Reviewed Date:** July 08, 2026

**What do you like best about Weights & Biases?**

It has easy experiment tracking and smooth integration with tools like PyTorch Lightning, which makes logging metrics and comparing runs very simple

**What do you dislike about Weights & Biases?**

The tracked-hours pricing can become expensive when running multiple experiments in parallel. The dashboard also slows down with large logs, and offline sync isn't always reliable after interrupted runs. Improving performance, sync stability, and making pricing more predictable would make the overall experience much better.

**What problems is Weights & Biases solving and how is that benefiting you?**

Earlier, we relied on Excel sheets and screenshots to track experiments, which made comparing models and managing runs quite messy. Now W&B automatically logs metrics, hyperparameters, resource usage, and predictions in one dashboard. Comparing runs is much easier, the whole team has better visibility, reports are easy to share, and hyperparameter sweeps have saved us a lot of manual effort while making experiments more reproducible.

  ### 11. Clear ML Experiment Tracking with Easy Integration and Reliable Versioning

**Rating:** 4.0/5.0 stars

**Reviewed by:** Verified User in Oil & Energy | Mid-Market (51-1000 emp.)

This reviewer's identity has been verified by our review moderation team. They have asked not to show their 
name, job title, or picture.


**Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user.

**Validated Reviewer:** Validated through a business email account

**Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review.

**Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review.

**G2 Icon:** Our network of Icons are G2 members who are recognized for their outstanding contributions and commitment to helping others through their expertise.

**Reviewed Date:** August 11, 2026

**What do you like best about Weights & Biases?**

They are experiment tracking dashboard makes it completely easier for us to compare training runs, metrics and other hyperparameters in one place. Integration requires only a few lines of code and works well with popular ml frameworks. The visualisations are very clear and particularly helpful when debugging model performance. Artefact and other registry which also provide reliable versioning for datasets and models. Overall, I would say it creates a strong shade workspace for ML teams.

**What do you dislike about Weights & Biases?**

This platform sometimes uh being overwhelming initially because it includes many features, dashboards and other configuration options. Organising projects also becoming bit difficult if the team does not establish consistent naming conventions early. Their interface can also Occasionally feels bit slower when loading projects contain a large number of runs. And some of their advanced collaboration along with the governance and deployment capabilities, are also limited to the paid plans. Pricing may become expensive for growing teams with extensive usage.

**What problems is Weights & Biases solving and how is that benefiting you?**

This platform replaces manual spreadsheets and scattered logs with the centralized record of every machine learning experiment. It also helps us to reproduce previous results by capturing metrics, parameters, system usage and other data set models. Comparing runs allows us to identify the best-performing configuration much faster. And our teams can review progress and share findings right on the spot without repeatedly exchanging files. This overall reduced the experimentation time and improved the collaboration throughout the model development life cycle.

  ### 12. Helps track ML experiments.

**Rating:** 4.5/5.0 stars

**Reviewed by:** Sangeeta S. | Data Scientist II, Mid-Market (51-1000 emp.)

**Validated Reviewer:** Validated through LinkedIn

**Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review.

**Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review.

**Reviewed Date:** August 24, 2026

**What do you like best about Weights & Biases?**

It is great that W&B allows me to track various machine learning experiments in one place. When training models like XGBoost, I can compare runs, parameters, and evaluation metrics without having to track everything separately. The dashboard also makes it easy to see which model is training better.

**What do you dislike about Weights & Biases?**

The UI might seem a bit complex at first because of the sheer number of features. For smaller projects, it offers more features than I actually need.

**What problems is Weights & Biases solving and how is that benefiting you?**

It helps me keep track of my model experiments so I don't forget which versions I tried, which parameters I used, and what results I obtained. Before using W&B, comparing model runs required digging through each individual run, which was very time-consuming. Now, I can quickly review the history and results of past experiments and make informed decisions while improving my models.

  ### 13. ML Experiment Tracking, Forward Deployment, and Open-Weight Models Made Easy

**Rating:** 5.0/5.0 stars

**Reviewed by:** Verified User in Biotechnology | Small-Business (50 or fewer emp.)

This reviewer's identity has been verified by our review moderation team. They have asked not to show their 
name, job title, or picture.


**Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user.

**Validated Reviewer:** Validated through a business email account

**Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review.

**Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review.

**Reviewed Date:** July 28, 2026

**What do you like best about Weights & Biases?**

Makes tracking training experiments and sharing training data with my team easy, with dashboards similar to Tensorboard and low performance overhead. Easy to get started with. Backs up data to the cloud and works from a remote cluster seamlessly. Plus offers support for purchasing cloud compute for LLM fine-tuning and FAAS.

**What do you dislike about Weights & Biases?**

It doesn't display large quantities of data well, and it's difficult to use some of the more complex visualizations. As a place for publishing/using models, HuggingFace has a larger library and simpler API. Cloud compute pricing is competitive but higher than competitors.

**What problems is Weights & Biases solving and how is that benefiting you?**

It helps us log ML training/evaluation data (though the Experiments and Reports features) remotely as I work on an HPC cluster. I can access the data anytime through the mobile app or website, which is convenient because we don't need a secure connection to the cluster. We can also save model weights/architectures and publish them online alongside our academic papers.

  ### 14. Makes Comparing AI Experiments Easy, with Everything in One Place

**Rating:** 4.5/5.0 stars

**Reviewed by:** Prerna T. | Junior Recruiter, Mid-Market (51-1000 emp.)

**Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user.

**Validated Reviewer:** Validated through a business email account

**Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review.

**Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review.

**Reviewed Date:** August 27, 2026

**What do you like best about Weights & Biases?**

It makes it much easier to compare different AI experiments I performed. I don't have to manually keep track of different results or parameters, so it helps everything to simply be in one place.

**What do you dislike about Weights & Biases?**

I dislike that sometimes it can get very overwhelming when we go towards advanced features like custom dashboards, Artifacts etc.

**What problems is Weights & Biases solving and how is that benefiting you?**

It helps me in keeping track of different AI/ML experiments I performed. For me, it is not possible to always remember which model or experiment worked the best and what were the specific results. So, it helps me in that a lot.

  ### 15. Solid MLOps platform for experiment tracking with great collaboration features

**Rating:** 4.0/5.0 stars

**Reviewed by:** Dhruv P. | Product Manager, Mid-Market (51-1000 emp.)

**Validated Reviewer:** Validated through a business email account

**Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review.

**Source: G2 invite:** Invitation from G2. This reviewer was offered a nominal gift card as thank you for completing this review.

**Reviewed Date:** July 28, 2026

**What do you like best about Weights & Biases?**

Excellent experiment tracking and visualization dashboard that makes it easy to compare model runs and parameters. Strong integrations with major ML frameworks and seamless team collaboration features. The API is intuitive and well-documented, making it straightforward to log metrics and artifacts.

**What do you dislike about Weights & Biases?**

Pricing scales steeply with team size, which can be a barrier for smaller organizations. The learning curve for advanced features like custom dashboards and reports is moderate, and documentation could be more comprehensive for edge cases. Occasional UI/UX inconsistencies across different features.

**What problems is Weights & Biases solving and how is that benefiting you?**

Helps organize and track ML experiments systematically, reducing time spent manually managing experiment logs and parameters. Enables better collaboration across teams by centralizing model run history and results. Improves reproducibility and debugging of models by maintaining complete audit trails. Accelerates model iteration cycles and provides visibility into which hyperparameters yield the best performance.

  ### 16. Essential for Model Performance Monitoring

**Rating:** 4.5/5.0 stars

**Reviewed by:** Tayyab N. | Lead Machine Learning Engineer, Small-Business (50 or fewer emp.)

**Validated Reviewer:** Validated through Google using a business email account

**Incentivized:** This reviewer was offered a nominal gift card as thank you for completing this review.

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**Reviewed Date:** August 27, 2026

**What do you like best about Weights & Biases?**

I really appreciate how easy it is to track logs and compare model runs all in one place with Weights & Biases. The dashboard is clean, and it lets me monitor the progress of training remotely, which is super helpful. I also like that looking at metrics in run time helps catch errors faster. The initial setup was fairly easy too.

**What do you dislike about Weights & Biases?**

I find the pricing a bit high for smaller teams, and it takes me some time to learn how to effectively use the advanced features.

**What problems is Weights & Biases solving and how is that benefiting you?**

I use Weights & Biases to monitor log performance, compare parallel experiments, and quickly spot training errors. It's easy to track logs and compare model runs all in one place.

  ### 17. Scalable and Accessible, but a Cluttered UI and Pushy Pricing

**Rating:** 3.5/5.0 stars

**Reviewed by:** Ayush A. | Partner, Mid-Market (51-1000 emp.)

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**Reviewed Date:** August 27, 2026

**What do you like best about Weights & Biases?**

Democratization, ergo scalability. Whether you use it as a student or as a professional, it can become a standard platform—if you know what I mean.

**What do you dislike about Weights & Biases?**

It’s a cluttered UI, and the pricing makes it feel like they’re afraid you’ll leave, so they try to squeeze more out of you.

**What problems is Weights & Biases solving and how is that benefiting you?**

It helps reduce audit risk by providing complete data on what was done, such as which experiments were run. This makes it easier to see whether employees are wasting resources.
and learning too - older runs can teach new staff

  ### 18. AI Tracing and Evaluation Made Easy

**Rating:** 4.5/5.0 stars

**Reviewed by:** Clarion I. | GenAI Specialist Consultant, Small-Business (50 or fewer emp.)

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**Reviewed Date:** July 22, 2026

**What do you like best about Weights & Biases?**

AI tracing feature for most AI models and evaluation.

**What do you dislike about Weights & Biases?**

The free plan has limited features hence the need to upgrade to ensure one gets all features for deploying AI models.

**What problems is Weights & Biases solving and how is that benefiting you?**

AI inference, tracing and evaluation

  ### 19. Automatic Metrics Tracking, but Overall Experience Needs Improvement

**Rating:** 2.5/5.0 stars

**Reviewed by:** Verified User in Automotive | Enterprise (> 1000 emp.)

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**Reviewed Date:** July 30, 2026

**What do you like best about Weights & Biases?**

Automatically records metrics, code versions, making results better

**What do you dislike about Weights & Biases?**

Projects can get cluttered over time, and that can feel overwhelming.

**What problems is Weights & Biases solving and how is that benefiting you?**

Keeps records and training for every run. 
Helps identify changes

  ### 20. Effortless Training Run Tracking Made Simple

**Rating:** 4.5/5.0 stars

**Reviewed by:** Mamoon K. | Machine Learning Research Intern, Small-Business (50 or fewer emp.)

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**Reviewed Date:** December 03, 2025

**What do you like best about Weights & Biases?**

It helps track training runs easily. I can see all the logged runs in one place without manually checking

**What do you dislike about Weights & Biases?**

There should be an easy way to discard non useful runs.

**What problems is Weights & Biases solving and how is that benefiting you?**

The problem of manually checking training runs again and again in the code makes it tedious. For people learning code like me Weights and Biases presents a unique alternative

  ### 21. Seamless Integration and Reliable Support: A Daily Essential for Machine Learning

**Rating:** 5.0/5.0 stars

**Reviewed by:** Amir Masoud N. | Graduate Demonstrator, Small-Business (50 or fewer emp.)

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**Reviewed Date:** March 08, 2025

**What do you like best about Weights & Biases?**

It is highly and well integrated with libraries I am using like PyTorch Lightning. Many times I have set that up because it was very easy, and after a while, it has happened that I lost part of my results, and W&B helped me to easily recover them through the logs, which without it, I probably wouldn't have. The next and very important feature to me is that I can use many different machines and servers at the same time and without being worried about gathering all results together, then using tools like TensorBoard, having them online without any effort(most of the time saves me when I am using supercomputers). It is part of my daily tools, and when I am teaching students machine learning, in very early sessions after teaching them visualization, I will have them use W&B to repeat whatever they have learned so far. I have never had any problem with W&B, but I have heard from one of my friends, whom I recommended he use W&B, that customer support is very fast and experienced.

**What do you dislike about Weights & Biases?**

Sometimes it is bothering me when I am looking for very basic functionality of W&B and it doesn't provided good documentation for that.

**What problems is Weights & Biases solving and how is that benefiting you?**

Monitoring training models is an integral part of my research ad W&B made it easy for me.

  ### 22. Very useful quite powerful tool

**Rating:** 4.0/5.0 stars

**Reviewed by:** Verified User in Research | Small-Business (50 or fewer emp.)

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**Reviewed Date:** March 24, 2025

**What do you like best about Weights & Biases?**

Easy of use, ease of implementation, the possibility to gather all my results, ease of sharing results with teammates, It can compare a lot of data interactively which in other cases could be hard to implement

**What do you dislike about Weights & Biases?**

It is online approach which is both strong and weak side, sometimes servers are bit laggy.

**What problems is Weights & Biases solving and how is that benefiting you?**

It makes easy for me to store and analyze experiments results, which in case of using own implementation approach using matplotlib for example would require quite a lot of work.

  ### 23. Review for wandb

**Rating:** 4.5/5.0 stars

**Reviewed by:** Simon S. | AI Solutions Architect, Small-Business (50 or fewer emp.)

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**Reviewed Date:** January 28, 2025

**What do you like best about Weights & Biases?**

I like the flexibility to log custom parameters, and the colorful comparisons between models in for instance confusion matrices.

**What do you dislike about Weights & Biases?**

There are a couple of features I would have liked, such as the ability to set a global normalization flag, or controlling which windows stay on screen on reload, maybe these features exist, in that case I just haven't been able to find them

**What problems is Weights & Biases solving and how is that benefiting you?**

We build image classification software, and for that it is very useful to track model performance

  ### 24. WandB - the best online tool for experiment logging so far

**Rating:** 4.5/5.0 stars

**Reviewed by:** Ivan G. | Scientific Researcher, Small-Business (50 or fewer emp.)

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**Reviewed Date:** December 03, 2024

**What do you like best about Weights & Biases?**

We are a small team of 15 researchers. After the years of usage tensorboard, we decided to try online tools. We tried a few of them and find out that WandB suits us best. We really like easy of use, the fact that experiments are easily sharable, and hyperparameter sweep option. Also the option to tag all your experiments and subsequent filtration of them is also great.

**What do you dislike about Weights & Biases?**

WandB provides an option to create a report from your experiments. It would be nice to use these reports in our papers, however, during the review period, papers should be anonymized but there is no option to anonymize the reports.

**What problems is Weights & Biases solving and how is that benefiting you?**

Experiments sharing and logging

  ### 25. The fastest way to log your training runs

**Rating:** 5.0/5.0 stars

**Reviewed by:** Verified User in Research | Enterprise (> 1000 emp.)

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**Reviewed Date:** January 07, 2025

**What do you like best about Weights & Biases?**

Everything works almost out of the box and it has a "nice look" once logged in

**What do you dislike about Weights & Biases?**

I really can't resize images and masked images the way I want inside the GUI and looking at images on mobile is quite a nightmare

**What problems is Weights & Biases solving and how is that benefiting you?**

Logging my training runs. I could achieve the same result with tensorboard (and alike) + saving images and masks and periodically generating a webpage that shows them, but W&B already offers that and much more

  ### 26. Top-tier service for bargain bin prices

**Rating:** 4.0/5.0 stars

**Reviewed by:** Justin D. | Developer, Small-Business (50 or fewer emp.)

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**Reviewed Date:** July 26, 2024

**What do you like best about Weights & Biases?**

The hosted aspect is great and if you avoid storing large artifacts, too many histograms, or too many images, it's very cheap or free even for heavy usage. I often run training on remote systems and checking the eval outputs remotely can be a pain with other software like TensorFlow. You need to be sure to run the server on your instance to view the dashboard. With W&B you get comparably powerful features, and you don't need to do anything but run your train script. In addition to hosting, the Sweeps functionality is excellent for hyper-parameter sweeping and pre-determined groups of runs in multi-task settings.

**What do you dislike about Weights & Biases?**

Some UI elements, like the Runs data table, can be laggy, and sometimes the auto-refresh seems finicky.

**What problems is Weights & Biases solving and how is that benefiting you?**

W&B helps track and debug my experiments. I use it for developing new models, observing loss scales and adjusting them so they're in compatible ranges, detecting and addressing gradient instabilities such as vanishing or exploding. I also use it for hyper-parameter searching to find the best values for my training runs. Additionally, I use the Sweeps functionality for coordinating runs that involve many related models that are deployed together.

  ### 27. wandb works great and is very easy to setup and use supporting wide variety of media types

**Rating:** 4.5/5.0 stars

**Reviewed by:** Verified User in Biotechnology | Small-Business (50 or fewer emp.)

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**Reviewed Date:** July 09, 2024

**What do you like best about Weights & Biases?**

Ease of setting it up, the dashboard is pretty much each to use and allows to visualize a wide range of features at once. The integration is pretty much solid and works out of box for any script that I worked on

**What do you dislike about Weights & Biases?**

I used to pre train certain checkpoints in a sequential manner or sometimes my runs used to break in between due to memory/connection issues from there on it was quite difficult to visualize all the previous run in a single curve using the dashboard, setting the x axis as wall time helped but the curve was still not a single continuous graph

**What problems is Weights & Biases solving and how is that benefiting you?**

In some of my experiments I wanted to visualize how the grad norm varies with train iter or how does the learning rate scheduler affect the perplexity of the model that I am working on, wandb makes doing these experiments much easier

  ### 28. Weights and biases changed the way I interact with my models.

**Rating:** 5.0/5.0 stars

**Reviewed by:** Giannis Z. | PhD Candidate, Small-Business (50 or fewer emp.)

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**Reviewed Date:** September 10, 2024

**What do you like best about Weights & Biases?**

The best thing about W&B is that you don't need to think about performance visualization anymore. W&B handles that for you, no matter how many metrics you have or how complex they are. It's also very simple to use!

**What do you dislike about Weights & Biases?**

Can't think of anything that I dislike, my experience has been very positive until now.

**What problems is Weights & Biases solving and how is that benefiting you?**

Helps a lot with visualization and performance tracking.

  ### 29. WandMe

**Rating:** 4.5/5.0 stars

**Reviewed by:** Datta N. | Machine Learning Engineer 3, Small-Business (50 or fewer emp.)

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**Reviewed Date:** August 30, 2024

**What do you like best about Weights & Biases?**

The ability to track everything including gradients is a wonderful aspect.

**What do you dislike about Weights & Biases?**

One problem is if there's a zombie wandb process and I try to kill it, it makes other functioning training runs terminate.

**What problems is Weights & Biases solving and how is that benefiting you?**

To keep track of all the experiments and look at the comparisons anytime. Also share the plots and reports with the rest of the world.

  ### 30. W&B helped me increase my productivity

**Rating:** 5.0/5.0 stars

**Reviewed by:** Eshed R. | Senior Algorithm Architect, Enterprise (> 1000 emp.)

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**Reviewed Date:** February 22, 2024

**What do you like best about Weights & Biases?**

I like the WEB UI, especially the manipulation of plots and reports as they simplify and visualize many metrics and parameters. I also like the artifactory and the model registry, they help manage the countless number of models created during an ML/DL project. Sweep management is also cool! We build an automation tool around it that simplifies ML sweeps and thus helps us get better results. Finally, I love the prompt and kind assistance we (Nvidia) get on the dedicated Slack channel. Really appreciated!

**What do you dislike about Weights & Biases?**

Not too much actually :) I guess sometimes the web UI is a bit slow.

**What problems is Weights & Biases solving and how is that benefiting you?**

It solves the management of many (many many) ML experiments; helps us improve our KPIs and track this improvement. This is benefiting us by saving a lot of time on taking dev decisions based on results (i.e., decide on some algo change, set of hyper parameters).

  ### 31. Smooth workflow for AI benchmarks

**Rating:** 4.5/5.0 stars

**Reviewed by:** Bastien V. | PHD Student, Enterprise (> 1000 emp.)

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**Reviewed Date:** July 23, 2024

**What do you like best about Weights & Biases?**

The online API is really helpful to organize results and projects.

**What do you dislike about Weights & Biases?**

In the online website, the graphs showing evolution of a metric for example can't be dezoomed easily with the scroll wheel and we can't move in the graph after zooming.

**What problems is Weights & Biases solving and how is that benefiting you?**

It stores online my results and shows in live the logs. (without the need to run another command to visualize the results or refresh a page)

  ### 32. A no-brainer tool to assist in model training/evaluation/comparison

**Rating:** 5.0/5.0 stars

**Reviewed by:** Pe D. | Computer Vision Engineer, Small-Business (50 or fewer emp.)

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**Reviewed Date:** July 04, 2024

**What do you like best about Weights & Biases?**

Its easy and seamless integration with PyTorch lightening and simple API usage. The model (artifact) and logs logging also help me trace back a model that was training months ago.

**What do you dislike about Weights & Biases?**

Nothing as of now. Would appreciate more dark modes and API control to give experiment names, rather than having my experiment named 'Tasty-Aadvark'.

**What problems is Weights & Biases solving and how is that benefiting you?**

Having all my training sessions accessible from a single site is the biggest benefit. Also, saving logs, training meta is quite helpful too.

  ### 33. Great platform for DNN training support

**Rating:** 5.0/5.0 stars

**Reviewed by:** Verified User in Higher Education | Small-Business (50 or fewer emp.)

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**Reviewed Date:** December 09, 2024

**What do you like best about Weights & Biases?**

Visualization of data from different perspective

**What do you dislike about Weights & Biases?**

Nothing really, maybe it can be good to customize the hardware monitoring interval

**What problems is Weights & Biases solving and how is that benefiting you?**

It helps me learn the progress of my machine learning training jobs

  ### 34. Best software for ML experiment tracking

**Rating:** 5.0/5.0 stars

**Reviewed by:** Liam C. | Research Assistant, Small-Business (50 or fewer emp.)

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**Reviewed Date:** August 16, 2024

**What do you like best about Weights & Biases?**

- Ability to view in browser
- Ability to share with collaborators
- Ability to add figures to experiment reports

**What do you dislike about Weights & Biases?**

- Annoying bug with visualising segmentation labels - red speckles appear in the label masks which can make it hard to evaluate.

**What problems is Weights & Biases solving and how is that benefiting you?**

Tracking ML experiments and sharing with collaborators

  ### 35. I like the ease of setup, I know no viable alternative, I hate the slowness and numerous bugs

**Rating:** 3.5/5.0 stars

**Reviewed by:** Gaspard L. | Small-Business (50 or fewer emp.)

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**Reviewed Date:** April 09, 2024

**What do you like best about Weights & Biases?**

It is easy, I can live preview the results, all the plots are done automatically and smartly. It is a great gain of time.

**What do you dislike about Weights & Biases?**

The user interface is slow but it is acceptable. Retrieving runs data from wandb using the wandb.Api() takes forever (e.g., 30h for around 30 000 runs of hyperparameter in several environments). I would like to be able to download all data from a set of runs selected from filters in a single api call. Since it represents less than 100 mb of data, it should be feasible in a few minutes maximum, right? The documentation is not great.

**What problems is Weights & Biases solving and how is that benefiting you?**

Logging and visualization during development (since I am using wandb in research, I still have to redownload all data using wanbd.Api() at the end, because the wandb plot are not professional enough (bitmap instead of vectors)). It is saving me a enormous amount of time.

  ### 36. Easy to use, but super helpful tool for logging machine learning experiments

**Rating:** 4.5/5.0 stars

**Reviewed by:** Verified User in Manufacturing | Small-Business (50 or fewer emp.)

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**Reviewed Date:** June 13, 2024

**What do you like best about Weights & Biases?**

That it is super easy to log all metrics, loss curves and all different kind of data and to get that data visualized in an interpretable manner. I really like how it is integrated into other frameworks like eg pytorch lightning. I use W&B almost daily, at least I haven't started a single training run without using W&B ever since I subscribed.

**What do you dislike about Weights & Biases?**

1) I would like to customize the plots and visualizations of the metrics shown even more. That would be nice to be able to do by using a script or something that can be used across multiple projects --> eg I would like to determine (from my python script) the color of all lines in a plot, and I don't know how to do that. It would just be useful for communication to team leaders, bosses etc., if they knew that eg. accuracy would also be plotted with a red, dotted line and that recall would always be a thick, blue line or something like that. 2) I have a hard time figuring out how to navigate all artifacts and how to use those. In eg the integration with ultralytics W&B will create an artifact for each epoch, which quickly fills up my storage. However, that is just a minor thing as I have just created a stand alone script to delete artifacts that aren't tagged with "best" etc.

**What problems is Weights & Biases solving and how is that benefiting you?**

Before using W&B I would either use TensorBoard (hard to set up and won't log the same amount of data) or rely on the automatic logging from AWS SageMaker (which is crap). Both these older methods took really long time to setup which delayed all projects - and then we are not even talking about how hard it is to manage and remember "these files are from this run, these other files are from that other run" as that what needed before. Hence using W&B increases the frequency of which I can test new ideas by saving me so many hours each time I start on something new.

  ### 37. Perfect for seemless experiment tracking

**Rating:** 5.0/5.0 stars

**Reviewed by:** Kilian  F. | PhD student, Mid-Market (51-1000 emp.)

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**Reviewed Date:** July 25, 2024

**What do you like best about Weights & Biases?**

I use it for every project, it became a key tool for me to keep an overview about experiments no matter if or when using LLMs

**What do you dislike about Weights & Biases?**

Working in teams is limited in the free version

**What problems is Weights & Biases solving and how is that benefiting you?**

Experiment tracking which helps to keep track of trials

  ### 38. Great platform for collaboration of experiments with intuitive coding steps

**Rating:** 4.5/5.0 stars

**Reviewed by:** Shimon S. | Research squad lead, data science, Mid-Market (51-1000 emp.)

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**Reviewed Date:** August 19, 2024

**What do you like best about Weights & Biases?**

The API is self explanatory and the UI is smart

**What do you dislike about Weights & Biases?**

Caching management is not clear, dis not find a way to clean old logs

**What problems is Weights & Biases solving and how is that benefiting you?**

Sharing results, experiment tracking management

  ### 39. Weights & Biases

**Rating:** 5.0/5.0 stars

**Reviewed by:** Verified User in Research | Small-Business (50 or fewer emp.)

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**Reviewed Date:** April 15, 2024

**What do you like best about Weights & Biases?**

Much easier than tensorboard. Way easier to get started and then a lot more functionality once you're more experienced. Easy monitoring of gpu use. Very easy to compare runs. Easy to upload tables and images. Also easy to compare just the runs you want and to save working experiments in a nice format (reports)

**What do you dislike about Weights & Biases?**

The only downsides which I hope will be fixed at some point is you don't have an easy way of deleting just one run. Would be nice if you could restart a run from the step you left it at as well. But in the day to day use they're pretty minor and the positives outweigh the downsides.

**What problems is Weights & Biases solving and how is that benefiting you?**

I'm a researcher not a business so it's mainly helping me keep track of my research.

  ### 40. Very quick and easy to start online logging

**Rating:** 5.0/5.0 stars

**Reviewed by:** Verified User in Research | Enterprise (> 1000 emp.)

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**Reviewed Date:** June 27, 2024

**What do you like best about Weights & Biases?**

This tool is perfect for logging information from programs, especially during training. It allows you to see how your model is training from anywhere in the world. I like how you can just dump some raw data onto the platform, and then you can make your graphs and manipulate the data separately from your training loop.

**What do you dislike about Weights & Biases?**

Some features are missing but I am sure they would come if I did a feature request.

**What problems is Weights & Biases solving and how is that benefiting you?**

Logging data from machine learning training loops that may be running headless.

  ### 41. Wandb works well out of the box

**Rating:** 5.0/5.0 stars

**Reviewed by:** Verified User in Research | Small-Business (50 or fewer emp.)

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**Reviewed Date:** July 10, 2024

**What do you like best about Weights & Biases?**

Easy to plug in and use. Works well with PyTorch and lightning and easy to compare models when away from local network.

**What do you dislike about Weights & Biases?**

Can slow down training speed and there are some minor bugs sometimes when using on a less well supported device/framework. Mobile UI also slow.

**What problems is Weights & Biases solving and how is that benefiting you?**

Helping me compare models quickly on the go. A lot easier to use than other solutions and cloud syncing to share with others.

  ### 42. Great platform - saves me many hours of work for tasks that I've previously coded manually

**Rating:** 4.0/5.0 stars

**Reviewed by:** Verified User in Biotechnology | Small-Business (50 or fewer emp.)

This reviewer's identity has been verified by our review moderation team. They have asked not to show their 
name, job title, or picture.


**Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user.

**Validated Reviewer:** Validated through LinkedIn

**Source: Organic:** Organic review. This review was written entirely without invitation or incentive from G2, a seller, or an affiliate.

**Reviewed Date:** April 15, 2024

**What do you like best about Weights & Biases?**

Easy to use, already incorporated into major libraries, but still powerful.

**What do you dislike about Weights & Biases?**

The only thing I wish was different is pricing per "tracked hour". For my workflow, this number seems very inflated - I have a few powerful GPUs, and run multiple experiments at a time on each one. This results in "tracked hours" of many multiples of realtime, for each GPU, which doesn't seem right. This is OK for me now as an academic, on the personal plan with unlimited tracked hours, but discourages me from using this for commercial projects in the future, where cost would quickly become prohibitive.

**What problems is Weights & Biases solving and how is that benefiting you?**

Experiment tracking is hard, important, and wandb makes it almost trivial.

  ### 43. have recommended to others before, would again

**Rating:** 5.0/5.0 stars

**Reviewed by:** jimmy s. | undergrad researcher, Small-Business (50 or fewer emp.)

**Validated Reviewer:** Validated through a business email account

**Source: Organic:** Organic review. This review was written entirely without invitation or incentive from G2, a seller, or an affiliate.

**Reviewed Date:** July 09, 2024

**What do you like best about Weights & Biases?**

I first learned about w&b 5 years ago in high school, and used it for a few projects. I now use it every day and have convinced several colleagues in and out of the lab to use w&b.

**What do you dislike about Weights & Biases?**

i wish there was a way to locally/offline view the graphs, or at least be able to view graphs with latency.

**What problems is Weights & Biases solving and how is that benefiting you?**

easy system agnostic logging, and composting across runs

  ### 44. LLM training tracking

**Rating:** 5.0/5.0 stars

**Reviewed by:** Verified User in Mechanical or Industrial Engineering | Mid-Market (51-1000 emp.)

This reviewer's identity has been verified by our review moderation team. They have asked not to show their 
name, job title, or picture.


**Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user.

**Validated Reviewer:** Validated through Google using a business email account

**Source: Organic:** Organic review. This review was written entirely without invitation or incentive from G2, a seller, or an affiliate.

**Reviewed Date:** July 17, 2024

**What do you like best about Weights & Biases?**

I like how it seamlessly integrates into the workflow and reports all relevant information.

**What do you dislike about Weights & Biases?**

I did not like how it remains logged in even without the login command, and how it starts a different log for the same 'run name'.

**What problems is Weights & Biases solving and how is that benefiting you?**

Monitoring my multiple training logs, keeps all the plots in one place for easy access.

  ### 45. Easy-to-setup model logging product

**Rating:** 3.5/5.0 stars

**Reviewed by:** Verified User in Research | Enterprise (> 1000 emp.)

This reviewer's identity has been verified by our review moderation team. They have asked not to show their 
name, job title, or picture.


**Validated Reviewer:** Validated through a business email account

**Source: Organic:** Organic review. This review was written entirely without invitation or incentive from G2, a seller, or an affiliate.

**Reviewed Date:** April 09, 2024

**What do you like best about Weights & Biases?**

It is very quick to get started with logging models and performance to wandb, implementation and integration are readily intuitive and straightforward. There are some useful available features such as model sweeping and other filtering/grouping mechanisms with runs logged in a given project. Whenever I need to keep track of ML model performance, I use wandb.

**What do you dislike about Weights & Biases?**

The number of concurrent runs is somehow too limited if one launches jobs to a cluster. It is most of the time hard to find the relevant information you are seeking for in the documentation, hence help comes from issues dealt online by users on different platforms (github, stackoverflow, etc.)

**What problems is Weights & Biases solving and how is that benefiting you?**

- Logging performance of machine learning models - Helping the optimization of model hyperparameters It represents a large gain of time compared to manual logging and optimization.

  ### 46. Best existing machine learning experiment tracker, including a great hyperparameter tuning

**Rating:** 5.0/5.0 stars

**Reviewed by:** Manuel M. | Small-Business (50 or fewer emp.)

**Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user.

**Validated Reviewer:** Validated through a business email account

**Source: Organic:** Organic review. This review was written entirely without invitation or incentive from G2, a seller, or an affiliate.

**Reviewed Date:** February 21, 2024

**What do you like best about Weights & Biases?**

Extremely easy to use (both in browser or via API) + sweep launcher that allows to distribute experiments for different machines

**What do you dislike about Weights & Biases?**

There's no easy pipeline for cross-validation, unless you play a bit around... In any case, it does never get as smooth as the other default functionalities It is designed for the setting where you have fixed train, val, test sets

**What problems is Weights & Biases solving and how is that benefiting you?**

- Experiment tracker - Hyperparameter tuning (Sweep) Wandb makes integration of both aspects above quite easy in machine learning experiments

  ### 47. Pretty good and unique solution

**Rating:** 5.0/5.0 stars

**Reviewed by:** Verified User in Research | Enterprise (> 1000 emp.)

This reviewer's identity has been verified by our review moderation team. They have asked not to show their 
name, job title, or picture.


**Validated Reviewer:** Validated through Google using a business email account

**Source: Organic:** Organic review. This review was written entirely without invitation or incentive from G2, a seller, or an affiliate.

**Reviewed Date:** July 25, 2024

**What do you like best about Weights & Biases?**

Managing runs that are launched across different machines

**What do you dislike about Weights & Biases?**

All new accounts have to be a team not personal

**What problems is Weights & Biases solving and how is that benefiting you?**

Keep tracking of hyperparameter searches and evaluation metrics across different runs

  ### 48. Great product -- too expensive

**Rating:** 4.5/5.0 stars

**Reviewed by:** Tony T. | Small-Business (50 or fewer emp.)

**Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user.

**Validated Reviewer:** Validated through Google using a business email account

**Source: Organic:** Organic review. This review was written entirely without invitation or incentive from G2, a seller, or an affiliate.

**Reviewed Date:** February 21, 2024

**What do you like best about Weights & Biases?**

graphs, experiment logs, easy to share within team

**What do you dislike about Weights & Biases?**

too expensive. latency sometimes sucks too.

**What problems is Weights & Biases solving and how is that benefiting you?**

experiment tracking

  ### 49. great tool for tracking experiments

**Rating:** 4.5/5.0 stars

**Reviewed by:** Verified User in Consumer Electronics | Mid-Market (51-1000 emp.)

This reviewer's identity has been verified by our review moderation team. They have asked not to show their 
name, job title, or picture.


**Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user.

**Validated Reviewer:** Validated through Google using a business email account

**Source: Organic:** Organic review. This review was written entirely without invitation or incentive from G2, a seller, or an affiliate.

**Reviewed Date:** February 28, 2024

**What do you like best about Weights & Biases?**

i use it as my single point of knowledge for all my experiments results, including model weights, configs, false analysis etc

**What do you dislike about Weights & Biases?**

many specific use cases, which are not that specific imo, i had to implement myself,

**What problems is Weights & Biases solving and how is that benefiting you?**

easy experiment tracking

  ### 50. A Must Have Tool if You are a Serious ML Practitioner

**Rating:** 4.5/5.0 stars

**Reviewed by:** Reza S. | Data Scientist, Mid-Market (51-1000 emp.)

**Current User:** The reviewer uploaded a screenshot or submitted the review in-app verifying them as current user.

**Validated Reviewer:** Validated through Google using a business email account

**Source: Organic:** Organic review. This review was written entirely without invitation or incentive from G2, a seller, or an affiliate.

**Reviewed Date:** August 26, 2022

**What do you like best about Weights & Biases?**

W&B is so user-friendly and useful for any ML practitioner but if you are a serious one, you need to get your hands on this tool. Not only you can monitor the performance of your different architecture changes and hyper-parameters, but you can also debug some of the problems with your training. For example, one time I was pulling my hair understanding why my training is so slow, and just by looking at the system dashboard, I realized that CUDA had failed for some reason and I was training on CPU. The system dashboard is also so helpful to find the right batch size to make use of the last MBs of your VRAM, if you know what I mean ;) . All the different plotting options and model/hyper-parameter comparison capabilities, give you a lot of freedom and power to efficiently train machine learning models. 
I also appreciate the fact the product is constantly evolving and adapting in flow with the scene of AI. Their blog posts are also a treasure trove of ML knowledge which shows some top-notch serious ML people are working on the product.
All in all, go try it, it is fun and useful!

**What do you dislike about Weights & Biases?**

The UI has a very small delay in updating the progress of your training which you might find annoying if you are an impatient person. Also, I would have loved it if they could add other features like the estimated time to finish the training or even show the time scales of the training steps on the plots (maybe there is a way to activate it but did not find)

**What problems is Weights & Biases solving and how is that benefiting you?**

It takes away the need to write custom tools for monitoring your ML training and gives you the tools and capabilities to make your life a lot easier when you are a serious ML practitioner.


## Weights & Biases Discussions
  - [What is Weights & Biases used for?](https://www.g2.com/discussions/what-is-weights-biases-used-for) - 2 comments

- [View Weights & Biases pricing details and edition comparison](https://www.g2.com/products/weights-biases/reviews?section=pricing&secure%5Bexpires_at%5D=2026-10-02+05%3A35%3A08+-0500&secure%5Bsession_id%5D=dcdb1f07-d428-49cb-afaa-3ec92db5e94e&secure%5Btoken%5D=867ba263091b5b42a8b1b3f46eca22259910110294b25a6ca0c08d6fe27a22d1&format=llm_user)

## Weights & Biases Features
**Additional Functionality**
- Tagging
- Natural Language Processing
- Data Extraction
- Multi-Language
- Predictive Analytics
- Drag & Drop
- Speech Recognition
- Reporting/Analytics
- Data Storage Management
- Virtual Personal Assistant (VPA)
- AI Copilot
- Customer Segmentation
- Collaboration Tools
- Data Import/Export
- Generative AI
- For eCommerce
- Role-Based Permissions
- Customizable Branding
- Search/Filter
- Monitoring
- Document Management
- API
- Data Visualization
- Trend Analysis
- Machine Learning
- Access Controls/Permissions
- Alerts/Escalation
- Performance Metrics
- Real-Time Data
- Third-Party Integrations
- Mobile App
- Multiple Data Sources
- For Sales Teams/Organizations
- Sentiment Analysis
- Activity Dashboard
- Chatbot
- Workflow Automation

**Deployment**
- Language Flexibility
- Framework Flexibility
- Versioning
- Ease of Deployment
- Scalability

**Deployment**
- Language Flexibility
- Framework Flexibility
- Versioning
- Ease of Deployment
- Scalability

**Management**
- Cataloging
- Monitoring
- Governing
- Model Registry

**Operations**
- Metrics
- Infrastructure management
- Collaboration

**Management**
- Cataloging
- Monitoring
- Governing

**Generative AI**
- AI Text Generation
- AI Text Summarization

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