ort

pykeio/ort

Fast ML inference and training for ONNX models in Rust

GitHub Website

GraphCanon updated 1d · GitHub synced 1d

2.5k stars263 forksLast push 1d Rust Apache-2.0

Decision brief

ort accelerates ML inference and training tasks for ONNX models with high-performance Rust operations

Good fit when

When your project involves ONNX models that require fast inference times or efficient fine-tuning
If you prefer a tool built in Rust for better performance and memory safety compared to tools using other languages

Avoid when

When the primary development language is not compatible with Rust bindings
For projects requiring broad model support beyond ONNX, as ort specializes only in ONNX models and does not cover a wide array of formats like some competitors might

Observed Jul 15, 2026 · Source: enrich:decision_facts

ort alternatives Trust report

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Maintenance and security

Full trust report

Maintenance: Very active (0d since push); As of 1d
Provenance: Not a fork · Organization account; As of 1d
Security (OSV): No lockfile; As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

cargo add ort

crates.io

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

pykeio/ort offers high-performance operations for ONNX model inference and training written in Rust.

Capability facts

Languages: rust
Source: github.language · Aug 24, 2026

README

ort is a Rust interface for performing hardware-accelerated inference & training on machine learning models in the Open Neural Network Exchange (ONNX) format.

Based on the now-inactive onnxruntime-rs crate, ort is primarily a wrapper for Microsoft's ONNX Runtime library, but offers support for other pure-Rust runtimes.

ort with ONNX Runtime is super quick - and it supports almost any hardware accelerator you can think of. Even still, it's light enough to run on your users' devices.

When you need to deploy a PyTorch/TensorFlow/Keras/scikit-learn/PaddlePaddle model either on-device or in the datacenter, ort has you covered.

📖 Documentation

🤔 Support

🌠 Backers

💖 FOSS projects using `ort`

_{Open a PR to add your project here 🌟}

Text Embeddings Inference (TEI) uses ort to deliver high-performance ONNX Runtime inference for text embedding models.
Magika uses ort for neural network-based file type detection.
retto uses ort for reliable, fast ONNX inference of PaddleOCR models on Desktop and WASM platforms.
edge-transformers uses ort for accelerated transformer model inference at the edge.
sbv2-api is a fast implementation of Style-BERT-VITS2 text-to-speech using ort.
BoquilaHUB uses ort for local AI deployment in biodiversity conservation efforts.
CamTrap Detector uses ort to detect animals, humans and vehicles in trail camera imagery.
Ortex uses ort for safe ONNX Runtime bindings in Elixir.
oar-ocr A comprehensive OCR library, built in Rust with ort for efficient inference.
FastEmbed-rs uses ort for generating vector embeddings, reranking locally.
Ahnlich uses ort to power their AI proxy for semantic search applications.
Murmure uses ort as its core engine, leveraging NVIDIA Parakeet to deliver fully local, free, private and cross‑platform Speech‑to‑Text enhanced with LLM post‑processing.
Valentinus uses ort to provide embedding model inference inside LMDB.
SilentKeys uses ort for fast, on-device real-time dictation with NVIDIA Parakeet and Silero VAD.
**[Xybrid](https://github.com/xybrid-ai/xyb

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