tinygrad
Minimalist deep learning framework in under 10,000 lines of code.
About
tinygrad, maintained by the tiny corp, is a deep learning framework that sits between PyTorch and Karpathy's micrograd, kept intentionally small and hackable. It draws ergonomics from PyTorch, functional transforms from JAX, and scheduling ideas from TVM, using lazy evaluation to fuse operations into single kernels. It supports several GPU backends and can run real models while staying easy to read. Released under the MIT license.
Reviews (0)
Leave a Review
No reviews yet. Be the first to review!
Details
- Category
- AI Frameworks & Libraries
- Price
- Free
- Platform
- Local/Desktop
- Difficulty
- Intermediate (3/5)
- License
- MIT
- Added
- Apr 3, 2026
Related Tools
Unified system for large-scale distributed training and inference.
Guidance language for controlling LLM generation with constraints, grammars, and JSON schemas.
Library for easily accessing and processing ML datasets.
JAX neural network library with PyTorch-like module system.
High-level deep learning API supporting JAX, TensorFlow, and PyTorch backends.
Gradient boosting library by Yandex with native categorical feature handling.