Ollama leads in active contributors with 3 (30d); Fireworks AI leads in code adoption with 1 repos importing. Updated daily with live metrics.
Data sources: npm, PyPI, GitHub, Crunchbase, Hacker News, Reddit, job boards. Methodology →
Fireworks AI: 367.5K npm + PyPI downloads/mo (+11% MoM), 137 GitHub stars, 2 active contributors, 1 repos importing, $77M funded vs
Ollama: 410.9K npm + PyPI downloads/mo (+17% MoM), 165.8K GitHub stars, 3 active contributors, 671 dependents, 1 repos importing
Source: AI-Buzz Developer Adoption Index (DAI). Updated daily from 12 data sources. Methodology →
Ollama leads across 5 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: Ollama is depended on by 1.7K packages versus 49 for Fireworks AI. Ollama leads in package downloads with 410.9K per month compared to 367.5K for Fireworks AI (Ollama +17% MoM, Fireworks AI +11% MoM). Fireworks AI appears in 1 GitHub repositories compared to 1 for Ollama.
For growth trajectory: Ollama has 165.8K GitHub stars versus 137 for Fireworks AI. Ollama received 11 Hacker News mentions in the last 30 days compared to 1 for Fireworks AI.
For longevity/risk: Fireworks AI has raised $77M in total disclosed funding. Fireworks AI's most recent round was Series B. Ollama attracted 3 active contributors in the last 30 days compared to 2 for Fireworks AI. Fireworks AI operates in AI Infrastructure while Ollama focuses on Foundation Models.
Ollama leads on developer adoption with 410.9K monthly package downloads. Fireworks AI has 367.5K monthly downloads and is growing its developer footprint. For a deeper look, visit each company's full profile for trend charts, funding rounds, and community sentiment data.
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| Metric | Updated Mar 21 | Updated Mar 21 |
|---|---|---|
| Website | fireworks.ai → | ollama.ai → |
| Description | Fast and efficient generative AI inference platform | Run LLMs locally. Open-source tool for running models on your machine. |
| 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 (84%) | Excellent (94%) |
| 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 → | $77M | - |
| Last Funding | Series B Jul 2024 | - |
| Developer Adoption | ||
| Momentum | 31Moderate | 38Moderate✓ |
| npm Registry Downloads (30d) Source: npm registryUpdates: DailyNote: Includes all package installations including CI/CD pipelines and mirrorsMethodology → | 0 | 62.8K✓ |
| npm Trend (30d) | - | |
| PyPI Registry Downloads (30d) Source: PyPI (Google BigQuery)Updates: DailyNote: Includes all package installations including CI/CD pipelines and mirrorsMethodology → | 367.5K✓ | 348.1K |
| PyPI Trend (30d) | ||
| Total Downloads - npm + PyPI (30d) Source: npm + PyPI registriesUpdates: DailyNote: Sum of npm and PyPI; excludes other package managersMethodology → | 367.5K+11% | 410.9K+17%✓ |
| Active Contributors/Day Source: GitHub APIUpdates: DailyNote: Tracks designated public repos per company, not all company GitHub activityMethodology → | 2 | 3✓ |
| Contributors Trend | - | 0% |
| npm Dependents Source: Libraries.io APIUpdates: WeeklyNote: Counts direct and dev dependentsMethodology → | - | 671 |
| PyPI Dependents Source: Libraries.io APIUpdates: WeeklyNote: Counts direct reverse dependencies from PyPIMethodology → | 49 | 983✓ |
| Code Adoption (repos) Source: ecosyste.ms Packages APIUpdates: DailyNote: Approximate count; excludes forksMethodology →Exclusive | 1✓ | 1 |
| HN Discussion Share Source: Hacker News (Algolia API)Updates: DailyNote: Share of HN mentions within the company's primary categoryMethodology → | 0.4% of HN mentions | 3.9% of HN mentions |
| Status | Private | Private |
| HN Mentions (30d) Source: Hacker News (Algolia API)Updates: DailyMethodology → | 1 | 11✓ |
| HN Mentions Trend (30d) | ||
| Reddit Mentions (30d) Source: Reddit (search API)Updates: DailyNote: Counts posts/comments mentioning the company by nameMethodology →Exclusive | 0 | 13✓ |
| GitHub Stars Source: GitHub APIUpdates: DailyNote: Stars are bookmarks — a popularity signal, not a usage indicatorMethodology → | 137 | 165.8K✓ |
| Founded | 2023 | 2023 |
| Primary Category | ||
| Data Last Updated | ||
Data sources: npm, PyPI, GitHub, Crunchbase, Hacker News, Reddit, job boards. Methodology →
Licensed CC BY 4.0. Free to cite with attribution.
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: Ollama (62.8K).
Source: npm registry | Methodology | CC BY 4.0
| Date | Fireworks AI | Ollama |
|---|---|---|
| Feb 27 | - | 46.0K |
| Mar 6 | - | 56.6K |
| Mar 13 | - | 41.5K |
| Mar 20 | - | 0 |
| Mar 21 | - | 62.8K |
