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JAX (Google)

Framework Free

JAX is an open-source numerical computing library developed by Google Research that combines NumPy-style array operations with automatic differentiation, JIT compilation, and hardware acceleration across CPUs, GPUs, and TPUs for high-performance machine learning research. Its functional programming model and composable transformations including grad, jit, vmap, and pmap enable researchers to write expressive, mathematically clean ML code that runs efficiently at scale. JAX has become the primary research framework at DeepMind, Google Brain, and leading academic ML labs for frontier AI research where flexibility and performance are both critical.

💰 Pricing
Free
📂 Category
Framework
🏷️ Tags
ml framework, google, automatic differentiation, research
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