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About Weights & Biases
Weights & Biases is a set of developer tools for machine learning. It records experiments as models train so runs can be compared, supports model evaluation, and traces LLM applications.
Training code sends data to the hosted service, where results are viewed and shared in a web dashboard. It suits individuals and teams who want a record of their experiments without running their own tracking server.
Strengths
- Experiment tracking and comparison in one dashboard
- Covers both classic ML training and LLM tracing
- Results are easy to share with a team
Limitations
- Requires an account and sends data to a hosted service
- Proprietary platform
Details
- Pricing
- FreemiumOffers free use with paid plans for teams.
- License
- Proprietary
- Developer
- Weights & Biases
- Platforms
- Web
- How it runs
- Hosted service
- Account
- Required
- Best suited for
- ML practitioners who want hosted experiment tracking and LLM tracing
- Categories
- AI developer tools
- Last verified
- Added
- Sources
Alternatives to Weights & Biases
Compare allSoftware that can replace Weights & Biases for an important use case, and what changes if you switch.
MLflow
An open-source platform for tracing, evaluating and managing LLM applications, agents and machine learning models.
MLflow is an open-source Apache 2.0 platform covering classic model training plus LLM tracing and evaluation, which you host yourself instead of using a proprietary hosted service.
TensorBoard
A visualization toolkit for inspecting machine learning training runs, metrics and model graphs.
TensorBoard is a free open-source toolkit that charts training runs locally without an account, but it is oriented toward TensorFlow and has fewer collaboration features.
Langfuse
An open-source platform for tracing, evaluating and managing prompts for LLM applications and AI agents.
Langfuse is an open-source, self-hostable platform for LLM tracing, prompt management and evaluation, covering the LLM side but not classic ML experiment tracking.
LangSmith
A hosted platform for tracing, monitoring and evaluating LLM applications and AI agents.
LangSmith is a hosted proprietary platform for step-by-step agent tracing, online evals and cost tracking, focused on LLM apps rather than classic model training runs.
Opik
An open-source platform from Comet for debugging, evaluating and monitoring LLM applications and agents.
Opik from Comet is a free open-source platform for LLM tracing, evaluations and dashboards that can be self-hosted, but it does not cover classic ML experiment tracking.
Arize Phoenix
A self-hostable tool for tracing, evaluating and experimenting with LLM applications and agents.
Arize Phoenix offers self-hostable tracing, evals and experiments for LLM apps under a source-available license, running locally, in Docker or on Kubernetes rather than only hosted.
Similar software
Related functionality, not necessarily a direct replacement.
ZenML
An open-source framework for writing ML pipelines and AI agents in Python and running them on your own infrastructure.
Kubeflow
A Kubernetes-native set of open-source projects for running data, ML and AI workloads.
DeepEval
An open-source Python framework for unit-testing and evaluating the outputs of large language model applications.
Evidently
An open-source framework for evaluating, testing and monitoring LLM applications, RAG systems and ML models.
