Weights & Biases leads in npm + PyPI downloads at 509.5K/mo. Compare Arize AI, Langfuse, Weights & Biases across package adoption, contributors, funding, and discussion signals.
At a glance
Current leaders
Scan the current leaders here, then use the table below for the full comparison.
Downloads/mo
Weights & Biases
Next: Langfuse
509.5K
Dependents
Weights & Biases
Next: Langfuse
1.9K
Code adoption
Weights & Biases
Next: Arize AI
9.3K
Contributors/day
Arize AI
Next: Langfuse
4
Sources: npm, PyPI, GitHub, Crunchbase, Hacker News, Reddit, and job boards. Methodology →
Comparable data synced April 5, 2026Comparison table
Core adoption signals first, supporting context second. Gaps stay visible instead of being rounded away.
← Scroll to compare all 3 companies →
| Metric | Updated Apr 5 | Updated Apr 5 | Updated Apr 5 |
|---|---|---|---|
Adoption & EcosystemThese signals carry the most weight for a production default. | |||
| Momentum score | 32 Moderate | 43 Moderate | 47 Moderate |
| Total package downloads (30d)Source: npm + PyPI registriesUpdates: DailyNote: Sum of npm and PyPI; excludes other package managersMethodology → | 14.1K | 303.9K (2 packages) | 509.5K (2 packages) |
| npm registry downloads (30d)Source: npm registryUpdates: DailyNote: Includes all package installations including CI/CD pipelines and mirrorsMethodology → | 0 | 58.0K (2 packages) | 0 |
| PyPI registry downloads (30d)Source: PyPI (pypistats.org)Updates: DailyNote: Includes all package installations including CI/CD pipelines and mirrorsMethodology → | 14.1K | 245.8K (2 packages) | 509.5K (2 packages) |
| Package dependentsSource: npm + PyPI registriesUpdates: DailyNote: Counts dependent packages across tracked npm and PyPI packages.Methodology → | 12 npm 0 · PyPI 12 | 482 npm 128 · PyPI 354 | 1.9K npm 0 · PyPI 1.9K |
| Active contributors/daySource: GH ArchiveUpdates: DailyNote: Tracks designated public repos per company, not all company GitHub activityMethodology → | 4 | 2 | 2 |
| Code adoption (repos)Source: ecosyste.ms Packages APIUpdates: DailyNote: Approximate count; excludes forksMethodology →Exclusive | 4 | 4 | 9.3K |
Community & AttentionHelpful context, but weaker than the adoption rows above. | |||
| GitHub starsSource: GitHub GraphQL + GH ArchiveUpdates: DailyNote: Stars are bookmarks - a popularity signal, not a usage indicatorMethodology → | 9.2K | 24.4K | 10.9K |
| Hacker News mentions (30d)Source: Hacker News (Algolia API)Updates: DailyMethodology → | 0 | 0 | 1 |
| HN discussion shareSource: Hacker News (Algolia API)Updates: DailyNote: Share of Hacker News mentions within the company's primary category.Methodology → | Not tracked | 1% | 0.3% |
| Reddit mentions (30d)Source: Reddit (search API)Updates: DailyNote: Counts posts and comments mentioning the company by name.Methodology →Exclusive | Not tracked | Not tracked | 2 |
| Job mentions (30d)Source: Job board aggregationUpdates: DailyNote: Counts job listings that mention the company's technology.Methodology →Exclusive | Not tracked | 1 | Not tracked |
Company DurabilityCapital and financing history provide context, not the whole call. | |||
| Total disclosed fundingSource: Public records / manual researchUpdates: WeeklyMethodology → | $61M | $5M | $250M |
| Last funding round | Series B Sep 2022 | Seed May 2024 | Strategic Investment Nov 2023 |
Data TrustCoverage and freshness stay visible instead of being hidden by the narrative. | |||
| Data confidenceSource: AI-BuzzUpdates: DailyNote: Composite score based on field completeness, metric freshness, and identifier coverage.Methodology → | Excellent (94%) | Excellent (96%) | Excellent (90%) |
| Signals trackedSource: AI-BuzzUpdates: DailyNote: Number of tracked non-null signals in the core compare dataset.Methodology → | 4/7 adoption, attention, and trust signals | 5/7 adoption, attention, and trust signals | 6/7 adoption, attention, and trust signals |
| Latest sync | Apr 5, 2026 | Apr 5, 2026 | Apr 5, 2026 |
Verdict
Langfuse is the closest challenger, but the decision still depends on whether you care most about current footprint, durability, or upside.
Current adoption leader
Weights & Biases has the largest tracked package footprint at 509.5K/mo.
Code adoption leader
Weights & Biases also leads on tracked repository imports at 9.3K repos.
Funding cushion
Weights & Biases has the deepest disclosed funding base at $250M.
Attention signal
Weights & Biases currently leads Hacker News discussion at 1 mentions in the last 30 days.
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npm+PyPI downloads/mo: Weights & Biases 509.5K vs Langfuse 303.9K vs Arize AI 14.1K. GitHub stars: Langfuse 24.4K vs Weights & Biases 10.9K vs Arize AI 9.2K. code adoption repos: Weights & Biases 9.3K vs Arize AI 4 vs Langfuse 4. Data as of April 5, 2026. Source: AI-Buzz Developer Adoption Index, ai-buzz.com/compare/arize-ai-vs-langfuse-vs-weights-biases. Accessed April 5, 2026.
