Weights & Biases / wandb.ai
MLOps platform for tracking machine learning experiments, visualising model performance, and managing datasets and model versions in a collaborative environment.
Free plan
Yes
API access
Yes
Open source
No
Platforms
5
Weights & Biases (W&B) has become the standard experiment tracking platform in machine learning research and production, used at major AI labs, research universities, and enterprise ML teams worldwide. The platform addresses a practical problem that anyone who has trained machine learning models recognises: keeping track of which hyperparameters, datasets, and code versions produced which results.
The core feature is experiment tracking. By integrating a few lines of Python code into a training script, W&B automatically logs metrics, hyperparameters, model checkpoints, and system metrics throughout the training run. The resulting dashboard allows comparison of multiple experiment runs side by side to identify which configurations produce the best results, visualise training curves, and understand model behaviour.
W&B Weave, added more recently, extends the platform to LLM application development, providing tracing, evaluation, and monitoring for AI applications built with language models. This positions W&B as an evaluation and observability layer for the LLM application development workflow alongside traditional ML experiment tracking.
The collaboration features allow research teams to share experiment results, compare findings, and work together on model development in a way that is substantially better than sharing screenshots of training curves in Slack.
W&B is free for individual use with unlimited projects, which is how it has built a large community of researchers and practitioners. The Teams plan at $50/user/month adds collaboration features suitable for professional ML teams.
Weights & Biases runs as ml platform software built around code and text workflows. Users typically start with a prompt, upload, or connected data source, and the underlying model handles the heavy lifting before returning a result you can refine or export. It's available on web, python, and r, with API access for teams that want to embed it into their own products.
Recent YouTube videos cached from the backend so this page stays fast and fresh.
The capabilities that matter most for teams evaluating Weights & Biases.
Logs metrics, hyperparameters, and training curves from ML model training runs for comparison and analysis.
Automated hyperparameter optimisation that runs experiments across parameter spaces to find optimal configurations.
LLM application tracing and evaluation platform for monitoring language model applications in development and production.
Free for personal use with unlimited projects. Teams $50/user/month. Enterprise custom pricing with advanced security and compliance.
Model
Freemium
Starting price
$50/mo
Free trial
No
MLflow is a free open-source alternative for experiment tracking. Neptune.ai and Comet ML are competitor platforms. LangSmith focuses specifically on LLM application tracing and evaluation.
A side-by-side look at the closest alternative in this category.
Key facts about model providers, platforms, and team support.
Model Provider
Agnostic
Platforms
Web, Python, R, Julia, CLI
Deployment
SaaS, Self-hosted
Integrations
PyTorch, TensorFlow, Keras, JAX, Hugging Face, All major ML frameworks
Team Collaboration
Yes
Launch Year
2018
Compliance signals and data-handling notes as reported by the vendor.
SOC 2 Type II certified. Enterprise includes data handling agreements, private instances, and VPC deployment.
Review W&B's data handling policy. Metrics and model data are logged to W&B's cloud by default. Self-hosted deployment available for full data control. Enterprise includes data processing agreements.
Editorial Verdict
Weights & Biases is the best choice for teams doing serious ML model training who need organised experiment tracking and team collaboration. For LLM application development specifically, W&B Weave provides tracing alongside LangSmith as a comparable alternative.
Last verified July 24, 2026.
The platform is widely regarded as the best-in-class experiment tracking solution and is recommended in most ML engineering curricula and tutorials. For teams doing serious model training, W&B has become standard infrastructure.
YouTube7:14Free for personal use with unlimited projects. Teams $50/user/month. Enterprise custom pricing with advanced security and compliance.
Free for most models and Spaces. Pro $9/month for private models, priority inference, and ZeroGPU. Enterprise Hub from $20/user/month for team collaboration and security.
SOC 2 Type II certified. Enterprise includes data handling agreements, private instances, and VPC deployment.
Enterprise Hub includes SSO, access controls, audit logs, and private infrastructure. SOC 2 compliant.
Review W&B's data handling policy. Metrics and model data are logged to W&B's cloud by default. Self-hosted deployment available for full data control. Enterprise includes data processing agreements.
Public models and datasets are openly accessible. Enterprise Hub provides private model storage with data handling agreements. Review individual model licences before commercial deployment.
Verified reviews from signed-in users, stored in the backend and averaged into this tool's rating.
Sign in to rate Weights & Biases and leave a review.
No other reviews yet — be the first to share how this tool performs in practice.