MLflow vs Scale AI
both compete in AI Infrastructure. Updated daily with live metrics.
MLflow vs
Scale AI: 71.2K downloads/mo (+31%), 821 GitHub stars, 3 active contributors, $15.9B funded
Source: AI-Buzz. Updated daily from npm, PyPI, GitHub, and Hacker News.
Key Differences
For production adoption: Scale AI is depended on by 4 packages. Scale AI has 71.2K package downloads per month (+31% MoM). Scale AI appears in 5 GitHub repositories.
For growth trajectory: Scale AI has 821 GitHub stars. Scale AI received 26 Hacker News mentions in the last 30 days.
For longevity/risk: Scale AI has raised $15.9B in total disclosed funding. Scale AI's most recent round was Series G. both companies operate in the AI Infrastructure category.
Bottom Line
Scale AI leads on developer adoption with 71.2K 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 → | scale.com → |
| Description | Open-source platform for the ML lifecycle including experiment tracking and model registry | Data labeling and AI infrastructure platform |
| Total Disclosed Funding Source: Public records / manual researchUpdates: Weekly | N/A | $15.9B✓ |
| Last Funding | Not available | Series G Jun 2025 |
| 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 | 71.2K✓ |
| PyPI Trend (30d) | - | |
| Total Downloads (30d) Source: npm + PyPI registriesUpdates: DailyNote: Sum of npm and PyPI; excludes other package managers | Not tracked | 71.2K+31%✓ |
| Active Contributors/Day Source: GitHub APIUpdates: DailyNote: Tracks designated public repos per company, not all company GitHub activity | N/A | 3✓ |
| Contributors Trend | - | +200%+ |
| PyPI Dependents Source: Libraries.io APIUpdates: WeeklyNote: Counts direct reverse dependencies from PyPI | N/A | 4✓ |
| Code Adoption (repos) Source: ecosyste.ms Packages APIUpdates: DailyNote: Approximate count; excludes forks | N/A | 5✓ |
| HN Discussion Share Source: Hacker News (Algolia API)Updates: DailyNote: Share of HN mentions within the company's primary category | - | 1.9% of HN mentions |
| Status | Unknown | Unknown |
| HN Mentions (30d) Source: Hacker News (Algolia API)Updates: Daily | N/A | 26✓ |
| Reddit Mentions (30d) Source: Reddit (search API)Updates: DailyNote: Counts posts/comments mentioning the company by name | N/A | 11✓ |
| 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 | 821✓ |
| Founded | Unknown | 2016 |
| 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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