RxInfer.jl
The facts below are what the maker publishes about RxInfer.jl, checked and dated. Our editors have not written about it yet.
Plans and prices
From RxInfer.jl's own pricing page, checked 12 Oct 2026.
| Plan | Price | What it gives you |
|---|---|---|
| RxInfer.jl | Free | MIT-licensed open-source Julia package |
The facts
Each one read from RxInfer.jl's own pages, with the date it was checked.
What it does
- Bayesian analysis
- Yeschecked 24 Sep 2026
- Deployment
- desktopchecked 24 Sep 2026
- Extensibility
- The project describes support for custom operations and extensions with custom nodes and message update rules.checked 12 Oct 2026
- Inference methods
- It supports exact and variational inference algorithms.checked 12 Oct 2026
- Installation
- RxInfer is an officially registered Julia package installable with Julia's package manager.checked 12 Oct 2026
- Julia ecosystem
- RxInfer is built around ReactiveMP.jl for message passing, GraphPPL.jl for model and constraint specification, and Rocket.jl for reactive programming.checked 12 Oct 2026
- License
- RxInfer.jl is an MIT-licensed open-source project.checked 12 Oct 2026
- Limit
- The documentation notes that not all message-passing rules have analytical solutions; some cases may require numerical approximations or a different model structure.checked 12 Oct 2026
- Model features
- Its documented features include hybrid models with discrete and continuous latent variables, factorization constraints, graph visualization, and custom plugins.checked 12 Oct 2026
- Modeling
- It uses GraphPPL.jl to specify probabilistic models and inference constraints.checked 12 Oct 2026
- Purpose
- RxInfer.jl is a Julia package for Bayesian inference on factor graphs using reactive message passing.checked 12 Oct 2026
- Python access
- Documentation describes a REST API and Python SDK through RxInferServer.jl and RxInferClient.py, maintained by Lazy Dynamics as third-party projects that are not actively maintained by the core team.checked 12 Oct 2026
- Python integration
- A separate, third-party RxInferServer.jl REST API and RxInferClient.py SDK provide a way to use RxInfer from Python; the core team says these projects are unmaintained by it.checked 12 Oct 2026
- Reactive engine
- ReactiveMP.jl provides its message-passing inference engine, and Rocket.jl provides reactive extensions for Julia.checked 12 Oct 2026
- Scale
- The maker says it is designed to scale to models with millions of parameters and observations.checked 12 Oct 2026
- Scale and extensibility
- The documentation describes scalability to models with millions of parameters and observations, and support for custom nodes and message update rules.checked 12 Oct 2026
- Scripting support
- Yeschecked 24 Sep 2026
- Session sharing
- Session sharing is optional; the docs say shared sessions contain metadata and errors, not actual data, and can be inspected locally.checked 12 Oct 2026
- Streaming
- Its inference API works with asynchronous infinite data streams as well as static datasets.checked 12 Oct 2026
- Streaming data
- The inference API works with asynchronous infinite data streams and static datasets.checked 12 Oct 2026
- Support
- The FAQ directs users to the documentation, GitHub Discussions, GitHub Issues, and regular community meetings for help.checked 12 Oct 2026
- Telemetry
- The package usage counter is enabled by default and records a timestamp, random UUID, and RxInfer and Julia versions; the docs say it collects no code or data and can be disabled.checked 12 Oct 2026
Money
- Free plan
- Yeschecked 24 Sep 2026
