#4040th of 56 in ML frameworks and libraries
burn
Rust tensor library and deep learning framework for training and inference
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- Stars
- 16.1k
- License
- Apache-2.0
- Last commit
- Oct 2026
- Last release
- Oct 2026
- Language
- Rust
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Overview
Burn is a Rust tensor library and deep learning framework with dynamic graphs, autodiff and automatic kernel fusion. Backends built on CubeCL target CUDA, ROCm, Metal, Vulkan, WebGPU and CPU, plus a pure-Rust Flex backend for Wasm and no_std. The same model code is used for training and deployment, and ONNX, PyTorch and Safetensors weights can be imported.
Who it is for: Rust developers training or deploying models across varied hardware
Strengths
- Same code trains and runs inference; no export step to ONNX or other runtimes
- Backends for CUDA, ROCm, Metal, Vulkan, WebGPU, CPU, Wasm and no_std
- Swap backends at runtime via Device; autodiff and fusion work as decorators
- Terminal training dashboard built on Ratatui, no external service needed
Weaknesses
- Rust only; smaller ecosystem and model zoo than PyTorch
- ONNX import supports only a limited set of operators
- Remote execution backend is marked Beta
- LibTorch backend was deprecated in 0.22.0 and removed from main
What it needs
- GPU optional
- Needs Rust toolchain
- Models: ONNX (import), PyTorch weights, Safetensors
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