MLflow vs Weights & Biases
both compete in AI Infrastructure. Updated daily with live metrics.
MLflow vs
Weights & Biases: 22.6M downloads/mo (+8%), 10.9K GitHub stars, 10 active contributors, $250M funded
Source: AI-Buzz. Updated daily from npm, PyPI, GitHub, and Hacker News.
Key Differences
For production adoption: Weights & Biases is depended on by 1.9K packages. Weights & Biases has 22.6M package downloads per month (+8% MoM). Weights & Biases appears in 9.3K GitHub repositories.
For growth trajectory: Weights & Biases has 10.9K GitHub stars. Weights & Biases received 3 Hacker News mentions in the last 30 days.
For longevity/risk: Weights & Biases has raised $250M in total disclosed funding. Weights & Biases's most recent round was Strategic Investment. both companies operate in the AI Infrastructure category.
Bottom Line
Weights & Biases leads on developer adoption with 22.6M monthly package downloads. Both compete in the AI Infrastructure space. For a deeper look, visit each company's full profile for trend charts, funding rounds, and community sentiment data.
Downloads (30d)
Disclosed Funding
GitHub Stars
Package Dependents
Repos Importing (code adoption)
HN Mentions (30d)
Momentum (0-100)
Data freshness notice: MLflow: no data freshness timestamp available.
← Scroll to compare →
| Metric | MLflow | Updated Mar 17 |
|---|---|---|
| Website | mlflow.org → | wandb.ai → |
| Description | Open-source platform for the ML lifecycle including experiment tracking and model registry | ML experiment tracking and model management platform. |
| Total Disclosed Funding Source: Public records / manual researchUpdates: Weekly | N/A | $250M✓ |
| Last Funding | Not available | Strategic Investment Nov 2023 |
| Developer Adoption | ||
| Momentum | N/A | 35Moderate✓ |
| npm Registry Downloads (30d) Source: npm registryUpdates: DailyNote: Includes all package installations including CI/CD pipelines and mirrors | N/A | 0 |
| PyPI Registry Downloads (30d) Source: PyPI (Google BigQuery)Updates: DailyNote: Includes all package installations including CI/CD pipelines and mirrors | N/A | 22.6M✓ |
| PyPI Trend (30d) | - | |
| Total Downloads (30d) Source: npm + PyPI registriesUpdates: DailyNote: Sum of npm and PyPI; excludes other package managers | Not tracked | 22.6M+8%✓ |
| Active Contributors/Day Source: GitHub APIUpdates: DailyNote: Tracks designated public repos per company, not all company GitHub activity | N/A | 10✓ |
| Contributors Trend | - | +200%+ |
| PyPI Dependents Source: Libraries.io APIUpdates: WeeklyNote: Counts direct reverse dependencies from PyPI | N/A | 1.9K✓ |
| Code Adoption (repos) Source: ecosyste.ms Packages APIUpdates: DailyNote: Approximate count; excludes forks | N/A | 9.3K✓ |
| HN Discussion Share Source: Hacker News (Algolia API)Updates: DailyNote: Share of HN mentions within the company's primary category | - | 0.2% of HN mentions |
| Status | Unknown | Private |
| HN Mentions (30d) Source: Hacker News (Algolia API)Updates: Daily | N/A | 3✓ |
| Reddit Mentions (30d) Source: Reddit (search API)Updates: DailyNote: Counts posts/comments mentioning the company by name | N/A | 2✓ |
| Job Mentions (30d) Source: Job board aggregationUpdates: DailyNote: Counts job listings mentioning the company's technology | N/A | 1✓ |
| GitHub Stars Source: GitHub APIUpdates: DailyNote: Stars are bookmarks — a popularity signal, not a usage indicator | N/A | 10.9K✓ |
| Founded | Unknown | 2018 |
| Primary Category | ||
| Data Last Updated | Unknown | |
* MLflow has no npm/PyPI packages tracked - download metrics unavailable. Signal score based on GitHub and community data only.
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