JAX
by Google Research · open-source · Last verified 2026-03-19
JAX is a numerical computation library developed by Google Research that combines Autograd and XLA to provide high-performance machine learning research. It offers automatic differentiation, GPU/TPU acceleration, and composable function transformations.
https://github.com/google/jax ↗B+
B+—Good
Adoption: B+Quality: A+Freshness: A+Citations: B+Engagement: B
Specifications
- License
- Apache 2.0
- Pricing
- open-source
- Capabilities
- automatic-differentiation, gpu-acceleration, tpu-acceleration, function-transformation
- Integrations
- Flax, Equinox
- Use Cases
- scientific-computing, deep-learning-research, high-performance-computing, numerical-simulation
- API Available
- Yes
- Tags
- machine-learning, numerical-computation, python, google, automatic-differentiation
- Added
- 2026-03-19
- Completeness
- 100%
Index Score
75.5Adoption
70
Quality
95
Freshness
90
Citations
75
Engagement
65
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