PyTorch vs JAX

The best value in each numeric row is marked. Sponsorship has no effect on any of them.

Comparison of PyTorch vs JAX
Criteria PyTorch
9 94.1 =
JAX
68 86.0 =
Score 94.1 (best) 86.0
Release freshness 94.9 (best) 94.3
Adoption signals 83.6 (best) 76.0
Release freshness
Updated 47 days ago
Updated 49 days ago
Latest version 197412 · 2026-09-19jax-v0.11.2 · 2026-09-17
Pricing FreeFree
License Open sourceOpen source
Platforms
Linux ✓ ✓
macOS ✓ ✓
API only ✓ ✓
Windows ✓ -
Features
Integrations
Rank receipt: PyTorch
#9 overall · #1 in category
94.1/100
  1. Platform readiness +40.0 100.0 × 40%
  2. Release freshness +33.2 94.9 × 35%
  3. Adoption signals +20.9 83.6 × 25%
Data from GitHub Last sync Computed on Sponsorship weight 0%, never counted Read the full formula
Rank receipt: JAX
#68 overall · #4 in category
86.0/100
  1. Platform readiness +34.0 85.0 × 40%
  2. Release freshness +33.0 94.3 × 35%
  3. Adoption signals +19.0 76.0 × 25%
Data from GitHub Last sync Computed on Sponsorship weight 0%, never counted Read the full formula

Component values are before weighting. Read the full formula