tch-rs
Rust bindings for PyTorch's C++ API
Pricing
Free tier
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is tch-rs?
tch-rs provides Rust developers with access to the powerful deep learning capabilities of PyTorch through its C++ API, enabling high-performance machine learning applications.
Key differentiator
“tch-rs uniquely offers Rust developers seamless access to PyTorch's powerful capabilities, making it ideal for high-performance ML applications in a Rust environment.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
tch-rs leverages PyTorch's C++ API, which might be unfamiliar to Rust developers used to idiomatic Rust patterns.
The library has undergone significant refactoring in minor version updates, leading to the need for substantial code modifications by users.
As an open-source project with a niche user base, tch-rs may have slower response times for issues and feature requests compared to larger projects.
Setting up the development environment requires configuring both Rust and PyTorch C++ API dependencies, which can be error-prone and time-consuming.
Fit analysis
Who is it for?
✓ Best for
Rust teams needing to integrate PyTorch's capabilities directly into their projects
Developers looking for high-performance ML solutions in a Rust environment
✕ Not a fit for
Projects requiring direct Python integration with PyTorch (use PyTorch directly)
Teams preferring managed services or cloud-based deep learning frameworks
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Works well with
Next step
Get Started with tch-rs
Step-by-step setup guide with code examples and common gotchas.