ort

Library Featured

A safe Rust wrapper for ONNX Runtime 1.31 - Optimize and accelerate machine learning inference & training

Checked · Sources

Downloads
3,902,768
Dependents
694
Stars
2,611
Forks
279
Contributors
78
Commits
1,104
Latest release
2.0.0-rc.15 ·

About

From the project 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 🌟

Read the full README
  • 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.
  • nicegal is a desktop image gallery app that uses ort for OCR & semantic image search.
  • 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 uses ort to run LLMs, ASR, and TTS natively on-device across iOS, Android, Flutter, and Unity apps and games.
  • Ultralytics YOLO Rust Inference is a high-performance, pure Rust library and CLI providing a fast and efficient interface for running YOLO models using ort.
  • Air Paint uses ort to run a YOLO hand pose model for real-time air drawing.
Runs on
CUDA, WebGPU, ROCm
What shows it
  • CUDA: ort feature cuda, ort-sys feature cuda
  • WebGPU: ort feature webgpu, ort-sys feature webgpu
  • ROCm: ort feature rocm, ort-sys feature rocm
Native code
Required
  • Binds native code: onnxruntime, ort-sys
  • Build uses a native toolchain: pkg-config (feature pkg-config)
Python bindings
No Python binding crate found
License
Apache-2.0 OR MIT

Compare with similar projects

Order: strongest tier first, then most downloads, then name, with unmeasured values last. A library counts downloads over 30 days. An app counts binary downloads per release. An app with none counts its crate downloads over 30 days. ML Rust runs this catalogue, so its closest project always gets a row.

ort beside the projects that share a topic with it
ProjectDownloadsDependentsStarsLatest releaseRuns on (GPU)Native codeLicense
ort This page Featured

A safe Rust wrapper for ONNX Runtime 1.31 - Optimize and accelerate machine learning inference & training

3,902,768 downloads over 30 days 694 2,611 2.0.0-rc.15 CUDA, WebGPU, ROCm Binds native code: onnxruntime, ort-sys. Build uses a native toolchain: pkg-config (feature pkg-config) Apache-2.0 OR MIT
rten Featured

Tensor library for the RTen machine learning runtime

496,924 downloads over 30 days 29 360 0.27.0 GPU support unknown No native code found Apache-2.0 OR MIT
lele Listed

Bare-metal machine learning inference library in Rust

132 downloads over 30 days 1 183 0.2.0 GPU support unknown No native code found MIT
higgs App Listed

A rust mlx server, ui, and model router for fast, dependency free inference on apple architecture

23 binary downloads per release Not applicable 34 Not measured Not measured MIT
blazr App Listed

Inference server for LLMs, speech and embeddings: OpenAI-compatible routes with streaming, plus speech synthesis (TTS) and transcription (ASR). Serves Llama, Mistral, Qwen, Mamba2, MLA+MoE and hybrid models from SafeTensors, AWQ, GPTQ and GGUF.

8 binary downloads per release Not applicable 7 0.7.1 CUDA, WebGPU Binds native code: ring (feature distributed) Apache-2.0
orkhon Listed Dormant

Machine Learning Inference Framework and Server Runtime

Python bindings

0 downloads over 30 days 0 153 0.2.3 GPU support unknown No native code found MIT

Fast, unified, Rust-native, Axum-compatible inference endpoints and nervous system for tensor models and LLMs: KServe / Triton and OpenAI APIs from one pure-Rust server

241 downloads over 30 days 0 66 0.16.2 CUDA, WebGPU, Metal No native code found MIT
Why FeaturedIt passes every Featured gate.

What it meets

  • It has 409 active dependents and 385 new dependents in 365 days. Featured needs 11 active dependents or 9 new dependents in 365 days.
  • Active dependents are at 100% of their peak. Featured needs at least 50%.
  • Docs are present. The release commit or a manifest ties the crate to the repository.
  • No vulnerability advisory stays unpatched past the grace window. At least one version is outside 0.0.x.
  • The last activity is on 1 Nov 2026, 8 days ago. The rules expect an update within 800 days. Dormancy rule

What else the check found

  • Every version is a prerelease.

Exact rules: Featured library. The check on applied thresholds version 9.

Every rule outcome, as the check records it
  • expected-interval: version 2.0.0-rc.15 base 200, doubled for 3902768 downloads per month, doubled for 408.5 active users: E = 800 days
  • dormancy: last activity 2026-11-01, 8 days ago, E = 800: active
  • featured: featured: active_users 408.5, new_adopters 384.5, former_glory 1, every version is a prerelease
Crates5 crates

Measurements and sources

Each signal row shows the raw value, its source and the fetch date. The Sources list gathers every distinct source on this page. Movement needs more history.

Sources6 sources
Adoption409 active dependents, 385 new dependents in 365 days1 not measured
Adoption measurements
SignalValueSourceFetchedCounts
Active dependents408.5crates.io database dumpYes
New dependents (365 days)384.5crates.io database dumpYes
Peak active dependents404.5crates.io database dumpYes
Active dependents as a share of the peak1crates.io database dumpYes
Binary downloads per releaseNot measuredYes
MaintenanceLatest human commit: 8 days ago3 not measured
Maintenance measurements
SignalValueSourceFetchedCounts
Latest human commit2026-11-01GitHub repositoryYes
Latest release2026-10-23crates.io database dumpYes
First release2023-11-22crates.io database dumpYes
Latest version2.0.0-rc.15crates.io database dumpYes
Days the oldest outside issue waits for a reply22GitHub repositoryYes
Maintainer replies over 365 days82GitHub repositoryYes
Repository archivedfalseGitHub repositoryYes
Repository gonefalseGitHub repositoryYes
Release commit or manifest in the repotruecrates.io packageYes
Published docstruecrates.io database dumpYes
Latest release fails cargo checkNot measuredYes
Build check dateNot measuredYes
Build check toolchainNot measuredYes
SecurityUnpatched vulnerabilities: none
Security measurements
SignalValueSourceFetchedCounts
Unpatched vulnerabilities past the grace windownoneRustSec advisory databaseYes
RustSec unmaintained advisorynoneRustSec advisory databaseYes
Deprecation noticenonecrates.io database dumpYes
Deprecated requirementnonecrates.io database dumpYes
Distribution16 releases, 3,902,768 downloads over 30 days5 not measured
Distribution measurements
SignalValueSourceFetchedCounts
Releases16crates.io database dumpYes
Downloads over 30 days3902768crates.io database dumpYes
Binary downloads over the last 3 releasesNot measuredYes
Homebrew installs on request over 365 daysNot measuredYes
Repology repository familiesNot measuredYes
Docker pull growth over 90 daysNot measuredYes
Docker pulls at the growth baselineNot measuredYes
Every version a prereleasetruecrates.io database dumpYes
Every version 0.0.xfalsecrates.io database dumpYes
Every version yankedfalsecrates.io database dumpYes
Crate deleted from crates.iofalsecrates.io database dumpYes
Repository2,611 stars, 279 forks, 78 contributors, 1,104 commits. Stars alone never qualify a project.
Repository measurements
SignalValueSourceFetchedCounts
GitHub stars2611GitHub repositoryYes — one part of the repository route
GitHub forks279GitHub repositoryYes — one part of the repository route
Contributors with a GitHub account78GitHub contributorsYes — one part of the repository route
Commits on the default branch1104GitHub repositoryNo
Repository's main crate left out of the entrynonecrates.io database dumpYes
Facts that never count
Facts that never count measurements
SignalValueSourceFetchedCounts
LicenseApache-2.0 OR MITcrates.io database dumpNo
Runs on, from listed crates and their direct dependenciesCUDA, WebGPU, ROCmcrates.io database dumpNo
What shows each backendCUDA: ort feature cuda, ort-sys feature cuda; WebGPU: ort feature webgpu, ort-sys feature webgpu; ROCm: ort feature rocm, ort-sys feature rocmcrates.io database dumpNo
Native code, from listed crates and their dependenciesBinds native code: onnxruntime, ort-sys. Build uses a native toolchain: pkg-config (feature pkg-config)crates.io database dumpNo
Python bindings, from direct dependencies of listed cratesNo Python binding crate foundcrates.io database dumpNo
Crates that depend on a listed crate directly694crates.io database dumpNo

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