OpenAI leads in npm + PyPI downloads at 46x; OpenAI has raised more funding at $171.7B; OpenAI leads in active contributors with 28 (30d); OpenAI leads in npm dependents with 11.3K; OpenAI leads in job demand with 2 mentions. Updated daily with live metrics.
Data sources: npm, PyPI, GitHub, Crunchbase, Hacker News, Reddit, job boards. Methodology →
CrewAI: 218.6K npm + PyPI downloads/mo (+5% MoM), 46.7K GitHub stars, 3 active contributors, 3 dependents, $18M funded vs
OpenAI: 10.1M npm + PyPI downloads/mo (+17% MoM), 30.3K GitHub stars, 28 active contributors, 11.3K dependents, 46.1K repos importing, $171.7B funded
Source: AI-Buzz Developer Adoption Index (DAI). Updated daily from 12 data sources. Methodology →
OpenAI leads across 6 of 7 key metrics
Downloads (30d)
Disclosed Funding
GitHub Stars
Package Dependents
Repos Importing (code adoption)
HN Mentions (30d)
Momentum (0-100)
For production adoption: OpenAI is depended on by 25.1K packages versus 548 for CrewAI. OpenAI leads in package downloads with 10.1M per month compared to 218.6K for CrewAI (OpenAI +17% MoM). OpenAI appears in 46.1K GitHub repositories.
For growth trajectory: CrewAI has 46.7K GitHub stars versus 30.3K for OpenAI. OpenAI received 79 Hacker News mentions in the last 30 days.
For longevity/risk: OpenAI has raised $171.7B in total disclosed funding, while CrewAI has raised $18M. CrewAI's most recent round was Series A, while OpenAI's most recent round was Venture. OpenAI attracted 28 active contributors in the last 30 days compared to 3 for CrewAI. CrewAI operates in AI Agents while OpenAI focuses on Foundation Models.
OpenAI leads on developer adoption with 10.1M monthly package downloads. CrewAI counters with 46.7K GitHub stars. For a deeper look, visit each company's full profile for trend charts, funding rounds, and community sentiment data.
← Scroll to compare →
| Metric | Updated Mar 21 | Updated Mar 21 |
|---|---|---|
| Website | crewai.com → | openai.com → |
| Description | Framework for building AI agent teams. Orchestrates multiple AI agents. | AI company behind ChatGPT, GPT models, and the OpenAI API |
| Data Confidence Source: AI-BuzzUpdates: DailyNote: Composite score (0-100) based on field completeness, metric freshness, and identifier coverage. Higher = more reliable data.Methodology → | Excellent (95%) | Excellent (92%) |
| Signal Coverage Source: AI-BuzzUpdates: DailyNote: Number of non-null adoption metrics tracked. Companies with more signals have more reliable composite scores.Methodology → | 5/7 metrics | 7/7 metrics |
| Total Disclosed Funding Source: Public records / manual researchUpdates: WeeklyMethodology → | $18M | $171.7B✓ |
| Last Funding | Series A Oct 2024 | Venture Feb 2026 |
| Developer Adoption | ||
| Momentum | 39Moderate | 64Moderate✓ |
| npm Registry Downloads (30d) Source: npm registryUpdates: DailyNote: Includes all package installations including CI/CD pipelines and mirrorsMethodology → | 216 | 2.4M✓ |
| npm Trend (30d) | ||
| PyPI Registry Downloads (30d) Source: PyPI (Google BigQuery)Updates: DailyNote: Includes all package installations including CI/CD pipelines and mirrorsMethodology → | 218.3K | 7.7M✓ |
| PyPI Trend (30d) | ||
| Total Downloads - npm + PyPI (30d) Source: npm + PyPI registriesUpdates: DailyNote: Sum of npm and PyPI; excludes other package managersMethodology → | 218.6K+5% | 10.1M+17%✓ |
| Active Contributors/Day Source: GitHub APIUpdates: DailyNote: Tracks designated public repos per company, not all company GitHub activityMethodology → | 3 | 28✓ |
| Contributors Trend | -1 contributors | +27% |
| npm Dependents Source: Libraries.io APIUpdates: WeeklyNote: Counts direct and dev dependentsMethodology → | 3 | 11.3K✓ |
| PyPI Dependents Source: Libraries.io APIUpdates: WeeklyNote: Counts direct reverse dependencies from PyPIMethodology → | 545 | 13.8K✓ |
| Code Adoption (repos) Source: ecosyste.ms Packages APIUpdates: DailyNote: Approximate count; excludes forksMethodology →Exclusive | 0 | 46.1K✓ |
| HN Discussion Share Source: Hacker News (Algolia API)Updates: DailyNote: Share of HN mentions within the company's primary categoryMethodology → | 21.2% of HN mentions | 21.5% of HN mentions |
| Status | Private | Private |
| HN Mentions (30d) Source: Hacker News (Algolia API)Updates: DailyMethodology → | 0 | 79✓ |
| HN Mentions Trend (30d) | ||
| Reddit Mentions (30d) Source: Reddit (search API)Updates: DailyNote: Counts posts/comments mentioning the company by nameMethodology →Exclusive | 1 | 21✓ |
| Job Mentions (30d) Source: Job board aggregationUpdates: DailyNote: Counts job listings mentioning the company's technologyMethodology →Exclusive | 1 | 2✓ |
| GitHub Stars Source: GitHub APIUpdates: DailyNote: Stars are bookmarks — a popularity signal, not a usage indicatorMethodology → | 46.7K✓ | 30.3K |
| Founded | 2024 | 2015 |
| Primary Category | ||
| Data Last Updated | ||
Data sources: npm, PyPI, GitHub, Crunchbase, Hacker News, Reddit, job boards. Methodology →
Anthropic's Claude Sonnet Leads New Practical AI Benchmark
Mar 12, 2026
GPT-5.4: OpenAI Pivots to High-Performance Specialist AI
Mar 7, 2026
LangChain vs OpenAI: New PyPI Data Shows Adoption Shift
Mar 6, 2026
OpenAI GPT-5.4: Single-Prompt Full-Stack App Generation
Mar 6, 2026
LangChain vs OpenAI: Python Adoption Data Reveals Shift
Mar 5, 2026
Which AI companies are developers actually adopting? We track npm and PyPI downloads for hundreds of companies. Get the biggest shifts delivered weekly.
Compare metric trends across companies over time
Comparing npm Downloads over 30 days: OpenAI (2.4M), CrewAI (216).
Source: npm registry | Methodology | CC BY 4.0
| Date | CrewAI | OpenAI |
|---|---|---|
| Feb 27 | 52 | 1.2M |
| Mar 6 | 34 | 1.4M |
| Mar 13 | 40 | 1.4M |
| Mar 20 | 0 | 0 |
| Mar 21 | 216 | 2.4M |
