Weights & Biases

Freemium

ML experiment tracking and model management platform with rich visualisations.

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Pricing

Freemium

Type

Automation

Languages

Python, JavaScript

// VERDICT

Reach for Weights & Biases when you want polished, managed experiment tracking and visualisation for ML, plus LLM evaluation via Weave. Skip it when you need fully open-source self-hosting (MLflow) or just lightweight prompt evals.

Best for

A managed platform for ML experiment tracking, visualisation and collaboration - logging runs, comparing experiments, and (via Weave) evaluating LLM apps, with a rich UI.

Avoid when

You want a fully open-source self-hosted tool, or only lightweight prompt evals.

CI/CD fit

SDK logging · managed platform · CI integration

Languages

Python · JavaScript

Team fit

ML/data-science teams · Research teams · Teams wanting rich experiment UIs

Setup

Easy

Maintenance

Low

Learning

Intermediate

Licence

Freemium

// BEST FOR

Tracking and visualising ML experiments richly
Comparing runs and hyperparameters
Collaboration and shareable dashboards
LLM app evaluation via Weave
Logging from training/eval with a few SDK calls
Reproducible, comparable experiments

// AVOID WHEN

You need fully open-source self-hosting (MLflow)
Only lightweight LLM prompt evals are needed
You can't send data to a managed service
Minimal/no-platform is preferred
You're not tracking experiments
On-prem-only is mandatory

// QUICK START

pip install wandb && wandb login
# wandb.init(); wandb.log({metric: value}) from training/eval
# use Weave for LLM-app evaluation

// ALTERNATIVES TO CONSIDER

Tool	Choose it when
MLflow	You want open-source, self-hostable lifecycle tracking.
Braintrust	Your focus is LLM evals with datasets and a UI.
LangSmith	You want LLM tracing + eval specifically.