
Starter
Tier 1: $50/user/mo from 250 to 5000 cumulative tracked hours*
Tier 2: $100/user/mo from 5,000 to 10,000 cumulative tracked hours*
Tier 3: $150/user/mo from 10,000 to 15,000 cumulative tracked hours*
Up to one team and 10 users per organization
Email and chat support
100 GB storage and artifacts tracking included. For additional storage, see prices.
Enterprise
Unlimited tracked hours* tracked
Dedicated Machine Learning Engineer & CSM to ensure success
Dedicated support channel
Support SLA
Custom storage plan
Single sign on
Service account for CI workflows
Personal
2 wandb server start
For personal projects only. Corporate use not allowed.
Unlimited experiments
Unlimited tracked hours*
100 GB storage and artifacts tracking included. For additional storage, see prices
Run a W&B server locally on any machine with Docker and Python installed
Enterprise
2 wandb server start
Unlimited tracked hours* tracked
Dedicated Technical Account Manager to ensure success
Dedicated support channel
Support SLA
Custom storage plan
Service account for CI workflows
Run a W&B server locally on your own infrastructure with a free enterprise trial license
Academic research teams
Use W&B to coordinate projects remotely, like Google Drive for machine learning.
create a teamManaged W&B Private Cloud
Need HIPAA compliance, or have data that can't leave your system? Install W&B locally, on your own servers.
Try W&B SERVERWhy use Weights & Biases?
Tired of pasting results into a spreadsheet? Track models automatically.
Debug model issues quickly with logs, charts, and tables of tracked results.
Quickly share findings and discuss model results with your team.
Use W&B’s reliable system of record to make all models reproducible.
Compare plans
Dashboard: Experiment tracking
Self-host your own installation of W&B for complete control of where data is visualized and stored.
Use W&B Teams to privately collaborate on ML projects and share results internally.
Artifacts: Data versioning
Automatically version logged datasets, with diffing and deduplication handled by Weights & Biases, behind the scenes.
Click through the UI to explore the relationship between a given dataset and the models in your pipeline, or identify all the precursor steps to a model you currently have in production.
Log and visualize predictions across models to identify issues in training, or find commonly misclassified examples that might need to be relabeled.
Sweeps: Hyperparameter optimization
Default sweeps dashboards are populated with a parallel coordinates chart and parameter importance panel, giving you fast access to insights about what hyperparameter combinations are the most effective.
Run automated sweeps to quickly find the best hyperparameters for your models, and use advanced features like early stopping to save compute resources.
Launch: ML workflow automation
Dashboard: Experiment tracking
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Artifacts: Data versioning
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Sweeps: Hyperparameter optimization
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Dashboard: Experiment tracking
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Artifacts: Data versioning
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Sweeps: Hyperparameter optimization
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Dashboard: Experiment tracking
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Artifacts: Data versioning
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Sweeps: Hyperparameter optimization
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Lineage & Tracking
Storage and Artifacts are free up to 100GB, then usage is billed monthly.
You have complete control of what is logged in W&B. You can curate and delete data from the system at any time.
Storage
The hosting costs of files saved to W&B servers
100 GB included free
$0.08 per GB up to 10 TB
$0.06 per GB up to 100 TB
$0.05 per GB up to 1000 TB
Artifacts
Files explicitly tracked with artifacts for reproducibility
100 GB included free
$0.05 per GB up to 10 TB
$0.03 per GB up to 100 TB
$0.02 per GB up to 1000 TB
Custom plans available.
Contact salesKey Values of
Weights & Biases
How our lightweight, interoperable tools empower your ML team
Reliable, automatic experiment tracking
Develop better models faster
Enable faster model development
Use the single, central system of record to save all the relevant metadata for your models automatically, so you can focus on model training. Spend more time in a flow state.
Debug model training seamlessly
Use live dashboards, with system metrics and terminal logs for each experiment, to understand bottlenecks and debug model training quickly, without hopping between tools.
Compare the latest results to previous baseline
Quickly understand what architecture and hyperparameter choices work, and focus on training new models. Avoid slowly digging through scattered files of manually-tracked results.
Key insights from experiment tracking
How are the latest experiments doing, compared to previous model versions?
Is this model running out of GPU memory? What are the system bottlenecks?
How does this hyperparameter affect accuracy across different classes?
What do sample predictions look like from this model?
Persistent knowledge base
Capture valuable insights centrally
A lab notebook for every ML experiment
Every time you run a new experiment, W&B captures the changes you made and gives you a place to jot down notes. Quickly compare your latest results with previous baselines.
Reproduce any experiment
Automatically track the exact version of the code, hyperparameters, and even the dataset your model trained on. Trace back exactly where your resulting models came from.
Transparent, understandable results
Annotate findings inside the central W&B system, so your models can speak for themselves. Use interactive notes, comments, and reports to clearly explain your research.
Key insights from a persistent knowledge base
Where are all the model files stored for this project?
What have we tried already, and what avenues should we explore next for improving this model?
What are the key findings from this research?
Machine learning team management
Move quickly on big projects, and make handoffs seamless
Easily track anywhere, on any infrastructure
Train on whatever compute is available - AWS, GCP, Azure, or the GPU box in the office. All results are organized in a central place.
Modular, interoperable solutions
Pick the tools that solve your problems best. With W&B, you're not locked in to an end-to-end platform. We pride ourselves on making our tools play well with other systems.
Stay focused on the hard problems
Spend more time in a flow state, and less time doing tedious tracking. With W&B, you can focus on the hard machine learning problems, and let us take care of tracking all the details to make the models reproducible.
Key insights from team management
How should new team members get started contributing to this ML project?
When someone leaves the team, how is their research saved and communicated?
How are all our projects doing, across the organization? Are any particular projects roadblocked or stuck? Are certain projects performing better than expected?
Production model lineage
Version and track every artifact in your model pipeline
Reproducibility at scale
Know where a model comes from end to end, and what is running where.
Dataset versioning
Reliably capture all changes to the data you're using to train your models.
Save datasets in any system: GCP, AWS, Azure, or even uploaded directly to W&B servers.
Clearly identify what downstream steps in your pipeline were affected by a change in data.
Model management
Capture all of your trained models in one central system.
Maintain a clear picture of all the data, preprocessing, and evaluation that was done on each model.
Trace back the lineage of any production model to the exact code and data that it was trained on.
Key insights from artifacts
What data was this production model trained on?
How did relabeling a chunk of data affect the accuracy of this model?
This data was corrupted — what downstream models were affected by this issue?
How did changing this preprocessing step affect model accuracy?