MLX (Apple) iconMLX (Apple)

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NumPy-like array framework optimized for Apple Silicon with lazy computation and composable function transformations

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Overview

MLX: An array framework for Apple silicon. Contribute to ml-explore/mlx development by creating an account on GitHub.

The Verdict

Who Should Use MLX (Apple)?

Best For

  • [Add best use case 1]
  • [Add best use case 2]
  • [Add best use case 3]

Not Ideal For

  • [Add limitation 1]
  • [Add limitation 2]

What's Great

  • NotificationsYou must be signed in to change notification settings
  • Fork1.9k
  • Star26.6k
  • Familiar APIs: MLX has a Python API that closely follows NumPy. MLX also has fully featured C++,C, a
  • Composable function transformations: MLX supports composable function transformations for automatic
Official Site

Watch Out For

  • [Research G2/Capterra for cons]
  • [Add con 2]
G2 Reviews

Pricing

Open Source
$0
MIT License - free and open source
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Key Features

  • NotificationsYou must be signed in to change notification settings
  • Fork1.9k
  • Star26.6k
  • Familiar APIs: MLX has a Python API that closely follows NumPy. MLX also has fully featured C++,C, a
  • Composable function transformations: MLX supports composable function transformations for automatic
  • Lazy computation: Computations in MLX are lazy. Arrays are only materialized when needed.

Platforms

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How It Compares

Feature MLX (Apple) Competitor 1 Competitor 2
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