--- title: Comet.ml Reviews meta\_title: 'Comet.ml Reviews 2026: Details, Pricing, & Features | G2' meta\_description: Filter 21 reviews by the users' company size, role or industry to find out how Comet.ml works for a business like yours. aggregate\_rating: rating\_value: 4.3 review\_count: 21 scale: '5' date\_modified: '2026-08-12' parent\_category: name: Artificial Intelligence url: https://www.g2.com/categories/artificial-intelligence --- # Comet.ml Reviews & Product Details Claimed ###### Profile Status This profile is currently managed by Comet.ml but has limited features. Are you part of the Comet.ml team? [Upgrade your plan](https://my.g2.com/comet-ml/upgrade?utm_campaign=s3&utm_medium=claim-popup&utm_source=g2) to enhance your branding and engage with visitors to your profile! Comet provides an end-to-end model evaluation platform for AI developers, with best in class LLM evaluations, experiment tracking, and production monitoring. * * * Seller [Comet.ml](https://www.g2.com/sellers/comet-ml) Discussions [Comet.ml Community](https://www.g2.com/products/comet-ml/discuss) Overview by Sarah Smith Show More ## Pricing Pricing provided by Comet.ml. ### Free Free ### Pro $39.00 Per Month [ View More Pricing Information ](https://www.g2.com/products/comet-ml/pricing) ## Top-Rated Alternatives [ ![Weights & Biases](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Weights & Biases") Weights & Biases 4.6/5(55) ](https://www.g2.com/products/weights-biases/reviews) [ ![Databricks](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Databricks") Databricks 4.6/5(1,365) ](https://www.g2.com/products/databricks/reviews) [ ![Gemini Enterprise Agent Platform](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Gemini Enterprise Agent Platform") Gemini Enterprise Agent Platform 4.3/5(745) ](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews) [ View All Alternatives ](https://www.g2.com/products/comet-ml/competitors/alternatives) ## User Insights Average based on 21 real user reviews. Typical contract price $0k - $0k [Sign in to view](/login) Per Month [Log in to unlock pricing and user insights](/login) ## Comet.ml Integrations (1) What do users say about integrations? Integration information sourced from real user reviews. [ ![Product Avatar Image](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Product Avatar Image") GitHub ](https://www.g2.com/products/github/reviews) Show More ![Anil B.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Anil B.") AB Anil B. Fresher Small-Business (50 or fewer emp.) 8/8/2026 Business partner of the seller or seller's competitor, not included in G2 scores. "Simple, All-in-One Machine Learning Experiment Tracking with Comet." 4.5/5 What do you like best about Comet.ml? The main thing that I like in Comet.ml is that it is really simple to track the results of my machine learning experiments. With Comet.ml, I can compare different models, track metrics, save the parameters, and organize the results of the experiments all in one place. The dashboards are useful for evaluating the performance of the models. Review collected by and hosted on G2.com. What do you dislike about Comet.ml? The reason why I don’t like the platform of Comet.ml is that there are some complex features which need some time to grasp. Besides, the interface might be quite complicated when dealing with several experiments and the need to configure some functions. I believe that the customization options of the reporting and dashboard can be more versatile. Review collected by and hosted on G2.com. What problems is Comet.ml solving and how is that benefiting you? Comet.ml addresses the issue of having to do all of the experiment management and comparisons manually. It stores all the experiment parameters, metrics, models, and results together in one place. This allows me to keep track of my progress, figure out which models work better, and replicate experiments more efficiently. Review collected by and hosted on G2.com. Show More Current UserValidated ReviewerIncentivizedSource: G2 invite ![Muhammed A.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Muhammed A.") MA Muhammed A. Technical Project Manager Information Technology and Services Small-Business (50 or fewer emp.) 7/31/2026 "Comet ML Makes Experiment Tracking and Collaboration Effortless" 4.5/5 What do you like best about Comet.ml? Keeping machine learning experiments organized becomes much easier with Comet ML. It provides clear visualizations for metrics, reliable experiment tracking, artifact management, and collaboration features that fit naturally into existing ML workflows. Comparing model iterations is straightforward, integrations with popular frameworks work smoothly, and the platform helps accelerate model development while improving reproducibility and team productivity. Review collected by and hosted on G2.com. What do you dislike about Comet.ml? Getting the most out of Comet ML requires some initial setup, especially when configuring advanced dashboards and collaborative workflows. As experiment histories grow, navigating large numbers of runs can become less convenient without additional filtering options. More flexible reporting, deeper customization of visualizations, and lower pricing for smaller teams would make the platform even more appealing. Review collected by and hosted on G2.com. What problems is Comet.ml solving and how is that benefiting you? Managing machine learning projects across multiple experiments used to involve spreadsheets, scattered logs, and manual tracking of model versions. Comet ML brings all of that into one centralized platform, making it easy to monitor training progress, compare results, and reproduce successful runs. The result has been faster experimentation, fewer mistakes when evaluating models, and a more efficient development process that allows the team to focus on improving model performance instead of managing experiment records. Review collected by and hosted on G2.com. Show More Our network of Icons are G2 members who are recognized for their outstanding contributions and commitment to helping others through their expertise.G2 IconCurrent UserValidated ReviewerIncentivizedSource: G2 invite ![Muhammad O.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Muhammad O.") MO Muhammad O. Salesforce Business Analyst Information Technology and Services Small-Business (50 or fewer emp.) 7/30/2026 "Simple and Reliable AI Experiment Tracking" 4/5 What do you like best about Comet.ml? What I like most about Comet.ml is how clearly it shows what’s happening behind the scenes in AI and LLM workflows. The interface feels well organized, and it’s easy to navigate through logs, traces, and experiment data all in one place. I also appreciate that it supports different AI frameworks, which makes debugging and monitoring a lot more manageable overall. Review collected by and hosted on G2.com. What do you dislike about Comet.ml? The biggest drawback for me is the learning curve when using it for the first time. Some of the observability and evaluation features can feel a bit advanced if you’re just getting started, which makes the initial setup and exploration less intuitive than it could be. A few guided tutorials or simpler onboarding examples would go a long way toward making the first experience smoother. Review collected by and hosted on G2.com. What problems is Comet.ml solving and how is that benefiting you? Comet.ml makes AI and LLM development easier by providing clearer visibility into experiments, logs, and overall model behavior. Rather than spending time manually tracking down issues, I can quickly see what happened during a run and pinpoint the areas that need improvement. It saves me time and keeps debugging and monitoring far more organized and consistent. Review collected by and hosted on G2.com. Show More Our network of Icons are G2 members who are recognized for their outstanding contributions and commitment to helping others through their expertise.G2 IconCurrent UserValidated ReviewerIncentivizedSource: G2 invite ![Jeni J.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Jeni J.") JJ Jeni J. Software Dev , Ai Agents Builder Information Technology and Services Mid-Market (51-1000 emp.) 7/28/2026 "Transforms Experiment Tracking with Ease" 4/5 What do you like best about Comet.ml? I use Comet.ml to track and compare machine learning experiments, monitor model training, and keep all my metrics, hyperparameters, and model versions organized in one place. I appreciate how it makes the entire development workflow much more reliable. The Comet.ml interface is clean and intuitive, and I love how easy it is to visualize and compare experiments without digging through logs or spreadsheets. The AI-powered observability tools for LLMs make it much easier to trace model behavior, identify issues, and improve performance with confidence. I really appreciate how well Comet.ml integrates with popular machine learning frameworks like PyTorch, TensorFlow, and Hugging Face, which makes adding experiment tracking to existing projects very seamless with just a few lines of code. Comet.ml automatically captures hyperparameters, metrics, model checkpoints, and training curves, saving me time and making it easier to reproduce results, compare runs, and collaborate with teammates. The initial setup was very easy for me. Review collected by and hosted on G2.com. What do you dislike about Comet.ml? One area that could be improved is the learning curve for some of the more advanced experiment management and observability features, as it can take a little time to understand everything the platform offers. I'd also like to see more customizable dashboards and reporting options, along with clearer cost visibility for larger teams managing many experiments and LLM evaluations. Review collected by and hosted on G2.com. What problems is Comet.ml solving and how is that benefiting you? I use Comet.ml to track and compare machine learning experiments, debug LLM applications, and organize metrics. It helps me reproduce results, debug performance issues, and collaborate efficiently, making the ML development workflow more reliable and reproducible. Review collected by and hosted on G2.com. Show More Our network of Icons are G2 members who are recognized for their outstanding contributions and commitment to helping others through their expertise.G2 Icon 7/30/2026 Current UserValidated ReviewerIncentivizedSource: G2 invite ![Verified User in Oil & Energy](/assets/icons/anonymous-avatar-purple-4ae1032bdb50ee5682003170c8184aee790d25958bd397abbd384ba52c596a7b.svg "Verified User in Oil & Energy") AO Verified User in Oil & Energy Mid-Market (51-1000 emp.) 8/10/2026 "Centralized ML Experiment Tracking with Clear Dashboards and Strong Reproducibility" 4/5 What do you like best about Comet.ml? This platform makes it easy to track and compare machine learning experiments all into a centralised workspace. I also like how it automatically records the needed parameters, metrics, code changes and other system information without even requiring any extensive support. Their dashboard provide clear visual comparison between the different model runs. It also helped our model registry and artefact versioning, improving the reproducibility and team collaboration. Overall, I would say this gave us better control over the complete model development life cycle. Review collected by and hosted on G2.com. What do you dislike about Comet.ml? Their interface can be bit overwhelming initially because of the number of features and configuration options available. And for large projects with multiple experiment may also require careful organization to keep their workspace manageable. Some advanced capabilities and other team management features are limited to higher priced plans and uploading extensive logs and artifacts can also add more storage and overhead the performance. Having a better onboarding and simpler cost visibility or transparency would improve the overall platforms experience. Review collected by and hosted on G2.com. What problems is Comet.ml solving and how is that benefiting you? This platform solves the difficulty of manually tracking model experiments across their spreadsheet and even, notebooks and disconnected tools. It gave us a reliable record of every model run and including its parameters, metrics code and other related artefacts. This allowed our team to reproduce successful experiments and understand why one model performs better than the other one. Their model registry also create a more structured process for promoting models into production, as a result of it our development became faster and more collaborative and less prone to repetitive work. Review collected by and hosted on G2.com. Show More Our network of Icons are G2 members who are recognized for their outstanding contributions and commitment to helping others through their expertise.G2 IconCurrent UserValidated ReviewerIncentivizedSource: G2 invite ![Arvind D.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Arvind D.") AD Arvind D. Software Engineer Enterprise (\> 1000 emp.) 8/5/2026 "Comet.ml Centralizes ML Experiment Tracking with Powerful Dashboards and Collaboration" 5/5 What do you like best about Comet.ml? What I like best about Comet.ml is how it centralizes the entire machine learning experimentation workflow. It automatically tracks experiments, hyperparameters, metrics, code versions, and system details, making it easy to reproduce results and compare different model runs. The interactive dashboards provide clear visualizations of training progress and performance, which helps identify improvements quickly. I also appreciate the seamless integration with popular ML frameworks, as it requires minimal setup and fits naturally into existing workflows. Collaboration is another major advantage—sharing experiments and reviewing results with team members is straightforward, improving transparency and reducing duplicated effort. Review collected by and hosted on G2.com. What do you dislike about Comet.ml? One area where Comet.ml could improve is the learning curve for new users. While it offers many powerful features, understanding the full range of experiment tracking, model management, and collaboration capabilities can take some time. For large projects with numerous experiments, the interface can occasionally feel overwhelming, and navigating extensive experiment histories could be more intuitive. Additionally, some advanced features are available only in higher-tier plans, which may be limiting for smaller teams or individual users. Improving customization options for dashboards and streamlining the user interface would further enhance the overall experience. Review collected by and hosted on G2.com. What problems is Comet.ml solving and how is that benefiting you? Comet.ml solves the challenge of managing and reproducing machine learning experiments by automatically tracking model parameters, metrics, code versions, datasets, and system configurations in one place. Instead of manually maintaining experiment logs, I can easily compare multiple training runs, identify the best-performing models, and reproduce results with confidence. It also simplifies collaboration by allowing team members to share experiment results and insights through a centralized platform. This has improved productivity, reduced time spent debugging and organizing experiments, and made the overall machine learning development process more efficient and reliable. Review collected by and hosted on G2.com. Show More Validated ReviewerIncentivizedSource: G2 invite ![TestZeus D.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "TestZeus D.") TD TestZeus D. Founding Growth Marketer Small-Business (50 or fewer emp.) 7/1/2026 "Comet.ml Makes Experiment Tracking Simple with Powerful Dashboards and Great Support" 4.5/5 What do you like best about Comet.ml? What I like best about Comet.ml is how simple it makess experiment tracking. When working on multiple ML experiments, it becomes very easy to lose track of parameters, metrics, model versions, and results. Comet.ml brings everything into one place and gives a clear view of what changed between runss. Seamless integrations throughout. The support is really great. The performance is amazing. AI enabled is also really good. The dashboaArd is also very helpful for comparing experiments side by side. It saves a lot of manual effort and makes collaboration smoother because the whole team can see the experiment history, performance trends, and outputs without digging through scattered files or notes. Review collected by and hosted on G2.com. What do you dislike about Comet.ml? There is a bit of a learning curve in the beginning, especially for someone who is new to experiment tracking platforms. Some workflows and integrations may take a little time to fully understand and set up properly. It would be helpful to have more guided onboarding examples for different types of ML projects, especially for beginners or smaller teams trying to adopt experiment tracking for the first time. Pricing can be more transparent. Review collected by and hosted on G2.com. What problems is Comet.ml solving and how is that benefiting you? Comet.ml helped us solve the problem of keeping ML experiments organized and reproducible. Earlier, it was really difficult for us to track which model version performed better, what parameters were used, or how one experiment compared with another. With Comet.ml, all the important experiment details like metrics, parameters, artifacts, charts, and results are stored in one place. This has made it easier for us to debug models, compare performance, share results with the team, and make faster decisions during model development. Overall, it has improved visibility, saved us a lot of time, and made the ML workflow much more structured. Review collected by and hosted on G2.com. Show More Validated ReviewerIncentivizedSource: G2 invite ![Rakesh G.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Rakesh G.") RG Rakesh G. Frontend Developer Small-Business (50 or fewer emp.) 8/12/2026 "Comet Makes ML Experiment Tracking and Team Collaboration Effortless" 5/5 What do you like best about Comet.ml? What I like most about Comet is how it helps me organize, compare, and reproduce ML experiments. It also has a clear dashboard and collaboration features, which make it much easier for the team to understand and stay aligned. Review collected by and hosted on G2.com. What do you dislike about Comet.ml? What I dislike is the complexity involved in tracking and setting up an experiment during the initial stage. Review collected by and hosted on G2.com. What problems is Comet.ml solving and how is that benefiting you? Comet solves the problem of managing ML experiments, metrics, parameters, and model versions all in one place. This makes it easier to compare results, and it helps me identify which approach is performing best. Review collected by and hosted on G2.com. Show More Current UserValidated ReviewerIncentivizedSource: G2 invite ![Verified User in Semiconductors](/assets/icons/anonymous-avatar-purple-4ae1032bdb50ee5682003170c8184aee790d25958bd397abbd384ba52c596a7b.svg "Verified User in Semiconductors") US Verified User in Semiconductors Mid-Market (51-1000 emp.) 5/19/2026 "Fascinating AI Agent Visualization That Brings Clarity to Debugging" 5/5 What do you like best about Comet.ml? The way Comet.ml visualizes the agents’ thought process is fascinating. Debugging AI agents has felt like a black box for quite a while, and Comet is helping me navigate that space with much more clarity. Review collected by and hosted on G2.com. What do you dislike about Comet.ml? I think the UI/UX could be improved a bit. The intuitiveness and the availability of quick-use buttons could be better. Also, the attempt to make it look like a GitHub interface is kind of unpleasing, although it’s still okay to work with. Review collected by and hosted on G2.com. What problems is Comet.ml solving and how is that benefiting you? Debugging of the AI agents, fixing them much earlier, sandboxing environments making it easier to test. Review collected by and hosted on G2.com. Show More Validated ReviewerIncentivizedSource: G2 invite SJ Shreyansh J. Mid-Market (51-1000 emp.) 2/8/2023 "Comet.ml: Streamlining Machine Learning and Collaborative Experiment Tracking Platform" 5/5 What do you like best about Comet.ml? Comet.ml provides an easy-to-use interface for tracking experiments, comparing results, and reproducing past results. This helps data scientists and machine learning engineers to keep track of their progress and make informed decisions based on their experiments. Comet.ml integrates with popular version control systems like Git, allowing users to track changes in their code and experiments over time. Review collected by and hosted on G2.com. What do you dislike about Comet.ml? Comet.ml may not be suitable for large-scale machine learning projects, as it has limited scalability compared to other solutions. Some users may find the platform's user interface and features to be limited, as it may not provide the level of customization they need for their projects. Review collected by and hosted on G2.com. What problems is Comet.ml solving and how is that benefiting you? Machine learning projects can involve a large number of experiments and it can be difficult to keep track of all the results and make decisions based on them. Comet.ml provides a platform for tracking experiments, comparing results, and reproducing past results, making it easier to manage machine learning projects. Review collected by and hosted on G2.com. Show More Validated ReviewerIncentivizedSource: G2 invite ## Pricing Options Pricing provided by Comet.ml. ### Free Free ### Pro $39.00 Per Month ### Enterprise Contact Us [ View More Pricing Information ](https://www.g2.com/products/comet-ml/pricing) Comet.ml Comparisons ![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/small_square/small_square_ee85a41e986e5c370efe084bbe07576b/weights-biases.png "Product Avatar Image") Weights & Biases 4.6/5(55) [ Compare Now ](https://www.g2.com/compare/comet-ml-vs-weights-biases) ![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/small_square/small_square_f70790069031a79320ca3574ae7f765d/clearml.png "Product Avatar Image") ClearML 4.7/5(13) [ Compare Now ](https://www.g2.com/compare/clearml-vs-comet-ml) ![Product Avatar Image](https://images.g2crowd.com/uploads/product/image/small_square/small_square_a6c205d533dba77b318af96d91beb2ac/databricks.jpeg "Product Avatar Image") Databricks 4.6/5(1,365) [ Compare Now ](https://www.g2.com/compare/comet-ml-vs-databricks) ##### ##### Comet.ml Features Deployment Language Flexibility Framework Flexibility Versioning Management Monitoring Operations Metrics [ View More Features ](https://www.g2.com/products/comet-ml/features) ##### Categories on G2 [MLOps Platforms](https://www.g2.com/categories/mlops-platforms) ##### Explore More [Which automotive digital retailing software uses AI to summarise calls and texts so managers can coach sales reps without reviewing every interaction manually?](https://www.g2.com/discussions/which-automotive-digital-retailing-software-uses-ai-to-summarise-calls-and-texts-so-managers-can-coach-sales-reps-without-reviewing-every-interaction-manually)[Which columnar databases are the easiest to integrate with Looker, Tableau and Google Data Studio so an analytics team can connect its BI tool without a complex connector setup?](https://www.g2.com/discussions/which-columnar-databases-are-the-easiest-to-integrate-with-looker-tableau-and-google-data-studio-so-an-analytics-team-can-connect-its-bi-tool-without-a-complex-connector-setup)[Which financial aid software platforms have strong customer support for families having difficulty with online applications?](https://www.g2.com/discussions/which-financial-aid-software-platforms-have-strong-customer-support-for-families-having-difficulty-with-online-applications) [Which lead retrieval systems have the strongest integrations with HubSpot and Salesforce so captured leads flow directly into the CRM without a CSV export step?](https://www.g2.com/discussions/which-lead-retrieval-systems-have-the-strongest-integrations-with-hubspot-and-salesforce-so-captured-leads-flow-directly-into-the-crm-without-a-csv-export-step)[What platform provides templates for business process mapping?](https://www.g2.com/discussions/which-platform-provides-templates-for-business-process-mapping)[What are the best contact center payments platforms combining digital phone lines with all-in-one service and 24/7 support?](https://www.g2.com/discussions/what-are-the-best-contact-center-payments-platforms-combining-digital-phone-lines-with-all-in-one-service-and-24-7-support) [Show MoreShow Less](javascript:void(0);)