W&B

About W&B

Financials

Dated, source-cited figures. Estimates are marked.

Products by W&B

All products by W&B reviewed by our AI panel of experts.

Weights & BiasesMachine Learning Platforms

Track, visualize, and reproduce your machine learning experiments

From $60/mo8.0/10

How Our Review Panel Scores W&B

Six independent reviewer personalities assessed W&B's product on their own terms. They disagreed by 1.0 points — The Finance Lead was the hardest to convince, The Domain Strategist the most positive.

Averaged across 1 reviewed product in our catalog. Scores are out of 10.

Competitive Landscape

Who W&B competes with, and how they differ.

MLflow8.5/10

Open-source and self-hostable, MLflow trades W&B's polished hosted dashboards and managed infrastructure for a lighter-weight, free tracking layer widely embedded in other MLOps stacks.

1 product reviewed on TopReviewed

Databricks8.4/10

Databricks bundles experiment tracking (via its stewardship of MLflow) into a full unified data-and-AI lakehouse platform, competing for MLOps budget with platform breadth rather than W&B's tracking-first depth.

1 product reviewed on TopReviewed

Comet7.4/10

Comet targets the same experiment-tracking and model-monitoring niche with a comparable free tier for individuals, but has meaningfully smaller enterprise market share and brand recognition than W&B.

1 product reviewed on TopReviewed

N

Neptune.ai

Neptune.ai is a smaller, venture-funded experiment tracker positioned as a lighter, lower-cost alternative to W&B for teams that don't need W&B's full model registry, prompt/eval tooling, and enterprise SSO.

Arize AI8.1/10

Arize focuses on production ML/LLM observability and monitoring after deployment, overlapping with W&B's newer Weave evaluation and tracing tools but starting from a different point in the ML lifecycle.

1 product reviewed on TopReviewed

ClearML7.8/10

ClearML is open-source-first with a self-hosted orchestration and pipeline-scheduling suite, competing on infrastructure control and on-prem deployment rather than W&B's managed SaaS convenience.

1 product reviewed on TopReviewed

Company Timeline

Key milestones in W&B's history, with sources.

1. Mar 4, 2025Acquisition

   CoreWeave agrees to acquire Weights & Biases

   CoreWeave announced it would acquire Weights & Biases in a deal reported at $1.7 billion by The Information, though the companies described the terms as undisclosed. The acquisition closed in May 2025.

   techcrunch.com
2. Aug 9, 2023Funding

   Raises $50M strategic round at $1.25B valuation

   W&B raised $50 million from Nat Friedman and Daniel Gross alongside existing investors Coatue, Insight Partners, Felicis, Bond, Bloomberg Beta and Sapphire, valuing the company at $1.25 billion and bringing total funding to $250 million.

   techcrunch.com
3. Oct 13, 2021Funding

   Raises $135M Series C at ~$1B valuation, led by Felicis

   Weights & Biases raised a $135 million Series C led by Felicis, with Insight Partners, Bond and Coatue participating, valuing the company at approximately $1 billion.

   techcrunch.com
4. Feb 1, 2021Funding

   Raises $45M Series B led by Insight Partners

   W&B raised a $45 million Series B round led by Insight Partners, with participation from Coatue, Trinity Ventures, and Bloomberg Beta.

   techcrunch.com
5. May 30, 2019Funding

   Raises $15M in second funding round, led by Coatue

   Weights & Biases raised $15 million, bringing total funding to $20 million, led by Coatue Management with angel participation from Nat Friedman and Richard Socher.

   techcrunch.com
6. May 31, 2018Funding

   Raises $5M Series A led by Trinity Ventures and Bloomberg Beta

   W&B raised a $5 million funding round to build its experiment-tracking developer tools for machine learning teams.

   techcrunch.com
7. 2017Founded

   Founded by Lukas Biewald, Chris Van Pelt, and Shawn Lewis

   Weights & Biases was founded in San Francisco in 2017 by Lukas Biewald, Chris Van Pelt, and Shawn Lewis (a former Google engineer) to build tools for tracking and reproducing machine learning experiments.

   wandb.ai