Weights & Biases

What is Weights & Biases?

Weights & Biases, often shortened to W&B or wandb, is a developer platform for teams that train models and build AI applications. The core product records experiments, versions datasets and models in an artifacts registry with lineage, and offers dashboards, tables and reports for comparing runs. W&B Weave extends this to LLM applications with tracing of inputs, outputs and metadata, evaluations, scorers, LLM-as-a-judge metrics and production monitoring. Newer pieces include W&B Inference for running open-source models and W&B Training for serverless fine-tuning and reinforcement learning, which is free during public preview. You can use the cloud, a privately hosted deployment, or run a local server with Docker for personal use. The Free plan is $0/mo, Pro starts at $60/month billed monthly with a 30-day free trial, and Enterprise is custom. Academic researchers can use it free with 200GB of cloud storage.

Use cases

• Track machine learning experiments
• Trace LLM calls and agent steps
• Evaluate LLM apps with scorers
• Version datasets and models
• Compare training runs on dashboards
• Fine-tune models with serverless RL
• Monitor LLM apps in production
• Self-host an experiment tracking server

Who it's for

• ML engineers
• AI application developers
• Research teams
• Enterprise AI teams
• Academic researchers

Why use Weights & Biases

• Experiment history, datasets and models live in one place with lineage, so runs are reproducible.
• Weave tracing makes LLM and agent behavior visible from a short instrumentation snippet.
• Evaluation and scoring tools let teams compare prompts, models and RAG setups on accuracy, latency and token use.
• A free tier and a free academic program lower the cost of getting started.
• Cloud, private hosting and local server options suit different security needs.

Weights & Biases features

• Experiment tracking for model training
• Artifacts registry with lineage tracking
• Weave tracing of LLM calls and agents
• Evaluations, scorers and LLM-as-a-judge metrics
• Production monitoring and PII data redaction
• Dashboards, tables and reports
• W&B Inference for open-source models
• W&B Training with serverless SFT and RL
• Team access controls and service accounts
• CI/CD automations with Slack and email alerts
• Self-hosted server with Docker
• SSO, audit logs and customer-managed encryption keys on Enterprise

Weights & Biases integrations

• Slack
• Docker
• CoreWeave
• AWS
• GCP

How to get started with Weights & Biases

1. Create a W&B account and install the library with pip install wandb.
2. Add a few lines to your training script, or instrument your LLM app with Weave, to log runs and traces.
3. Open dashboards, tables and traces to compare experiments and inspect each model call.
4. Set up evaluations and scorers, and add alerts or CI/CD automations on Pro.
5. Version datasets and models in the registry, or self-host the server with wandb server start.

Weights & Biases limitations

• Free plan allows up to 5 model seats, 5 GB storage and 1 GB of Weave ingestion per month
• Pro is meant for early-stage teams under 50 employees, and larger customers must move to Enterprise
• The Personal self-hosted plan is for personal projects only and bars corporate use
• Extra storage on Pro is $0.03/GB and extra Weave ingestion is $0.10/MB
• A site banner directs users who need to retrieve their data to customer support

Weights & Biases pricing

Yes, Weights & Biases has a free plan. Paid plans start at $60 per month, according to the official pricing page on 24 Oct 2026.

Weights & Biases plans

• Free

  $0/mo

  • AI application tracing and evaluations
  • Experiment tracking
  • Registry and lineage tracking
  • Community support

• Pro

  Starts at $60/month

  billed monthly, 30 day free trial

  • Unlimited teams
  • Team-based access controls
  • Service accounts
  • CI/CD automations
  • Priority email and chat support

• Enterprise

  Custom

  • Single tenant option
  • HIPAA compliant option
  • Single sign-on
  • Audit logs
  • Customer-managed encryption key

• Personal

  $0/mo

  Self-hosted, personal use only

  • 1 user seat
  • Experiment tracking
  • Registry and lineage tracking
  • Run server locally with Docker

• Advanced Enterprise

  Custom

  Self-hosted

  • Flexible deployment options
  • Single sign-on
  • Audit logs
  • Free enterprise trial license

Plans as listed on the official pricing page on 24 Oct 2026. Prices can change and may vary by country or exclude tax. Check the official pricing page.

Weights & Biases alternatives

The main Weights & Biases alternatives listed on Debuly are MLflow, Langfuse, Arize AX, Future AGI, Hugging Face and IBM watsonx.ai. The table compares pricing and platforms; order is A–Z.

1. 

   Arize AX

   Observability and evaluation platform for AI agents and LLM apps, with tracing, issue detection and experiments on a free plan.

   Developer platformsAutomation and agentsCoding
   FreemiumVisit Arize AX (official site)
2. 

   Future AGI

   Platform for tracing, evaluating, simulating and guarding LLM apps and AI agents, with a gateway, usage-based billing and a free tier.

   Developer platformsAutomation and agents
   FreemiumVisit Future AGI (official site)
3. 

   Hugging Face

   Hub for hosting machine learning models, datasets and demo Spaces, with pay-as-you-go inference, GPU hardware and team plans.

   Developer platformsCodingResearch and search
   FreemiumVisit Hugging Face (official site)
4. 

   IBM watsonx.ai

   IBM's AI development studio for building generative AI apps and agents with foundation models, prompt tools, and machine learning, billed by usage.

   Developer platformsCodingAutomation and agents
   FreemiumVisit IBM watsonx.ai (official site)
5. 

   Langfuse

   Open-source LLM observability and evaluation platform for tracing agents, managing prompts and scoring outputs.

   Developer platformsAutomation and agentsCoding
   FreemiumVisit Langfuse (official site)
6. 

   MLflow

   Open-source AI engineering platform for tracing, evaluating and deploying LLM agents, apps and classic ML models.

   Developer platformsAutomation and agentsCoding
   Open sourceVisit MLflow (official site)

Weights & Biases FAQ

Sources & verification

Facts on this page come from the official sources below, each with the date we read it. Written by Debuly; the vendor did not review this page.

Image credits

• Logo: from site.wandb.ai · fetched 24 Oct 2026 · Vendor trademark, used only to identify the product; removed on request
• Cover: none collected yet, so a generated tile is shown.

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