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Weights & Biases

ML experiment tracking and model management platform.

AI InfrastructureFounded January 2018#4 of 54 in AI Infrastructure

Updated May 29, 2026

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Company profile

What is Weights & Biases?

Weights & Biases is the standard tool for ML experiment tracking. Used by OpenAI, Anthropic, and thousands of ML teams. Raised $200M+ Series C at $1.25B valuation.

Company research

As of May 18, 2026
  1. Hacker News mentions increased 62.5% over the last 30 days. Hacker News is discussion volume, not adoption.

Source check
Standard. Use as a directional reading from retained source data.
Sources
Metric data from one provider.

Latest company data

Primary data point

Downloads

25.6M/30d

Tracked package: PyPI wandb

▲ +2%Updated 1d ago

Other data points

Dependent projects

2.1K

Projects depending on tracked package: PyPI wandb

Updated 9h ago

GitHub stars

11.1K

Main repository stars

Updated 9h ago

Hacker News

13/30d

Position #17 in category discussion

Updated 9h ago

Repository health

Maintenance data from the main open-source repository.

Key-person risk
2
External contributors
44
% of recent contributors outside the core team
Releases (30d)
0

Repository usage

Public repositories and source files importing packages tied to Weights & Biases.

Repos importing
9.3K0%

About Weights & Biases

Weights & Biases is the standard tool for ML experiment tracking. Used by OpenAI, Anthropic, and thousands of ML teams. Raised $200M+ Series C at $1.25B valuation.

FoundersLukas Biewald, Chris Van Pelt, Shawn Lewis

Funding

$250M · 5 rounds

Raised $250M total. Category position #4 of 54 in AI Infrastructure.

Strategic Investment2023

Daniel Gross, Nat Friedman

$50M
Series C2021

Felicis, Bond

$135M
Series B2021

Insight Partners

$45M
Series A2019

Trinity Ventures, Coatue

$15M
Seed2018

Trinity Ventures

$5M

Investors

BondCoatueDaniel GrossFelicisInsight PartnersNat FriedmanTrinity Ventures

Tracked packages (1)

1 PyPI

wandb

PyPIMain PyPI package

wandb

Track and version datasets, models, and other files used in ML workflows for reproducibility.