Plausible Analytics icon

Plausible Analytics

★★★★★ 4.6
VS

Weights & Biases

★★★★★ 4.7
Feature Plausible Analytics Weights & Biases
Pricing From $9/mo Free / from $50/mo
Free Plan ✗ No ✓ Yes
Rating 4.6 / 5 4.7 / 5
Best For privacy-conscious-businesses, bloggers, developers, eu-businesses ml-engineers, research-teams, ai-companies, data-scientists
Founded 2019 2017
Pageviews
Referrers
Goals
Custom Events
Utm Tracking
Api
Self Hosting
Experiment Tracking
Model Registry
Sweeps
Artifacts
Reports
Launch

✓ Plausible Analytics Pros

  • No cookies — GDPR compliant without consent banner
  • Script is under 1KB (vs GA's 45KB)
  • Open-source and transparent
  • Simple dashboard — no overwhelming data

✗ Plausible Analytics Cons

  • Less detailed than Google Analytics
  • No free tier (but affordable)
  • Limited segmentation and custom reports

✓ Weights & Biases Pros

  • Best-in-class experiment tracking
  • Beautiful visualizations
  • Great collaboration features
  • Generous free tier

✗ Weights & Biases Cons

  • Learning curve for full platform
  • Can be expensive for large teams
  • Requires integration work

The Verdict

Plausible Analytics is built for privacy conscious businesses and bloggers, with a focus on pageviews and referrers. Weights & Biases targets ml engineers and research teams and leads with experiment-tracking and model-registry.

On pricing, Plausible Analytics is the clear winner for budget-conscious users — starting at $9/mo compared to $50/mo for Weights & Biases. That $41/mo difference adds up quickly for growing teams.

Weights & Biases has a free plan, which gives it a meaningful edge for individuals and small teams exploring their options. Plausible Analytics requires a paid subscription from day one.

Feature-wise, Plausible Analytics offers broader built-in capabilities (7 features vs 6), while Weights & Biases takes a more focused approach — which can mean a simpler, faster onboarding experience.

This is a genuinely close comparison. If you can, sign up for both free trials (where available) and run a one-week test with your actual team tasks before deciding.

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