Tools · SPBoucher
Menu

Weights & Biases

by CoreWeave · Platform · also known as W&B, wandb, W&B Weave, CoreWeave Forge (umbrella brand)

ML experiment tracking, sweeps, artifacts and model registry plus Weave for LLM tracing and evaluation, now sold by CoreWeave within its Forge platform with a free academic tier

MIT licenseFreemiumPaidEnterpriseAcademicCloudSelf-hostedSelf-hostable
Visit official site Compare

Link verified Nov 2, 2026

Overview

Weights & Biases is a platform for tracking and comparing machine-learning work. The wandb Python SDK (MIT) logs metrics, configurations, gradients and media from training runs; Sweeps run hyperparameter searches; Artifacts and Registry version datasets and models; Tables and Reports provide interactive exploration and shareable dashboards. Weave extends the same account to LLM applications with traces, evaluations, a prompt playground and production monitors, and Serverless Inference exposes hosted open models. Integrations cover PyTorch, Keras, Hugging Face Transformers, Lightning and most training frameworks.

After CoreWeave acquired the company, the product became part of CoreWeave Forge; documentation moved to docs.coreweave.com and pricing to coreweave.com, while the Weights & Biases name and SDK remain. Plans are Free, Pro, Enterprise and Academic; Enterprise adds SSO, audit logs, customer-managed keys and dedicated or private hosting, and the Academic plan is free for researchers at academic institutions. W&B is a sensible default for experiment tracking in research groups, with the caveats that the hosted service is proprietary, that free-tier storage is limited, and that the ownership change has shifted URLs and branding, so older links may redirect.

Editorial note on uncertainty. license_spdx applies to the open-source wandb SDK; the hosted platform is proprietary. The wandb.ai root now redirects to forge.coreweave.com, so wandb.ai/site is recorded as the homepage.

Capabilities

  • Experiment tracking of metrics, configs, gradients and media
  • Sweeps for hyperparameter optimization
  • Artifacts and Registry for dataset and model versioning
  • Tables and Reports for exploration and sharing
  • Weave: LLM traces, evaluations, playground and monitors
  • Serverless Inference for hosted open models
  • Integrations with PyTorch, Keras, Transformers and Lightning

Typical workflows

  1. Log a fine-tuning run and compare it against earlier experiments
  2. Run a sweep across learning rates and report results
  3. Trace and evaluate an LLM agent with Weave

Strengths

  • Mature, widely adopted tracking SDK
  • Free academic plan
  • Experiment and LLM tooling under one account

Limitations

  • Proprietary hosted platform; self-managed deployment only for Enterprise
  • Free-tier storage and ingestion caps
  • Branding and URLs in flux after the CoreWeave acquisition

Prerequisites

  • W&B account and API key
  • Python training code to instrument

Who it is for

  • ML researchers and students
  • Teams training or fine-tuning models
  • LLM application teams using Weave

Alternatives & comparison

  • Braintrust

    Hosted observability and evaluation platform for AI agents with tracing, experiments, pattern detection, a CLI, MCP access and an AI assistant (Loop) that analyzes traces and builds evals

    MixedFreemium
  • Langfuse

    Open-source LLM observability and evaluation platform: tracing, LLM-as-judge and human evals, prompt management, datasets and cost dashboards, self-hostable or as Langfuse Cloud

    Open sourceOpen source
  • LangSmith

    LangChain's hosted platform for tracing, evaluating and deploying LLM applications and agents, with prompt tooling, an LLM gateway and cloud, hybrid or self-hosted options

    ProprietaryFreemium
Compare Weights & Biases with its alternatives →

Sources & verification

Primary sources consulted for this record. Claims are tied to the fields each source supports; the automated link checker re-verifies every URL on a schedule.

  • License
    wandb SDK license (MIT)

    https://github.com/wandb/wandb/blob/main/LICENSE

    Supports: license_spdx, source_model

    checked Nov 1, 2026
  • Official documentation
    Weights & Biases documentation (CoreWeave)

    https://docs.coreweave.com/products/wandb

    Supports: capabilities

    docs.wandb.ai redirects here

    checked Nov 1, 2026
  • Official site
    Weights & Biases

    https://wandb.ai/site

    Supports: name, summary, capabilities, vendor

    States that Weights & Biases is now part of CoreWeave Forge

    checked Nov 1, 2026
  • Pricing page
    https://coreweave.com/forge-pricing

    Supports: pricing_model

    Free, Pro, Enterprise, Academic

    checked Nov 1, 2026
Confidence
High
Reviewed
Nov 1, 2026
Links
Broken · Nov 2, 2026

Spotted an error?

Broken link, outdated license, wrong category, or a tool that no longer exists? Tell us; reports are reviewed by the editor.

MLX

Apple Inc. · Apple Silicon ML & MLX

In-depth entry

Apple's open-source array framework for machine learning on Apple Silicon, with NumPy-like Python, C++ and Swift APIs and unified CPU/GPU memory

MITOpen sourceFreeLocalNov 2, 2026

MLX LM

Apple Inc. · Apple Silicon ML & MLX

In-depth entry

Python package and CLI for running, serving, quantizing and fine-tuning large language models on Apple Silicon with MLX

MITOpen sourceFreeLocalNov 2, 2026

Ray

Ray project (Anyscale and contributors) · Distributed & parallel computing

In-depth entry

Open-source Python framework for distributing tasks, actors and ML workloads across a cluster, with libraries for data processing, training, tuning, serving and reinforcement learning

Apache-2.0Open sourceFreeLocalSelf-hostedBroken

Hugging Face Hub

Hugging Face · Training & fine-tuning

In-depth entry

Hosting platform for open models, datasets and Spaces demo apps built on git repositories and Xet storage, with Inference Providers, Endpoints, Jobs and an open-source Python client and CLI

MixedFreemiumPaidLocalNov 2, 2026

scikit-learn

scikit-learn developers · Mathematical & statistical computing

BSD-licensed Python machine-learning library for classification, regression, clustering, dimensionality reduction, preprocessing and model selection on NumPy and SciPy

BSD-3-ClauseFreeOpen sourceLocalNov 2, 2026

Sentence Transformers

Hugging Face · Embeddings, reranking & retrieval

Python library for computing and training embedding, cross-encoder reranker, sparse and multi-vector retrieval models, maintained by Hugging Face with thousands of pretrained models on the Hub

Apache-2.0Open sourceFreeLocalSelf-hostedNov 2, 2026