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Kinetic.jl

Free#22 of 89 in Physics Simulation Software

Kinetic.jl: Free, self-hosted Julia software for kinetic-flow research on CPUs or GPUs. Ranked #22 of 89 in Physics Simulation Software by our editors (6.9/10); pricing: Free plan; best for researchers simulating kinetic flows on CPUs or GPUs.

6.9/10Editor score
Kinetic.jl6.9 Visit Kinetic.jl

At a glance

  • Editor score
    6.9 / 10
  • Pricing
    Free plan
  • Best for
    Researchers simulating kinetic flows on CPUs or GPUs
  • Free plan
    Yes
  • Paid from
    Free
  • Delivery mode
    Desktop
  • Facts checked
    24 Sep 2026
Kinetic.jl screenshot
  • Where it wins

    • Handles Boltzmann, Euler, Navier–Stokes and other documented equations
    • Runs one- to three-dimensional simulations on CPUs and GPUs
    • Adds parallel execution, machine-learning methods and a Python interface
  • Where it doesn't

    • Requires a self-hosted Julia workflow and local technical setup
    • Focused on kinetic and fluid equations rather than general simulation domains
    • Support is centered on community channels and documentation

Our verdict on Kinetic.jl

Kinetic.jl is an open-source computational fluid dynamics toolbox written in Julia. It models particle transport and fluid-dynamics problems across kinetic theory and continuum mechanics, with support for Boltzmann, Euler, Navier–Stokes, Maxwell and other documented equations. One- to three-dimensional numerical simulations can run on CPUs or GPUs. The project is aimed at scientific research and educational work in kinetic theory, making it a fit for researchers and technically oriented teams who need direct control over simulation code.

The software is free and self-hosted, so there is no paid tier to compare. Its ecosystem is centered on Julia, with CUDA support for GPU execution, DifferentialEquations.jl and Flux integrations, and kineticpy for a Python interface. KitBase supplies physical models and numerical schemes, while KitML adds neural models and machine-learning methods. Parallel options include threaded and distributed execution. This combination suits workflows that already use Julia or need to connect Julia simulations with Python-based analysis.

Kinetic.jl’s standout strength is the breadth within its kinetic-flow focus: users can combine established equations, numerical schemes, CPU or GPU execution, and machine-learning approaches in one toolbox. The trade-off is a self-managed workflow that assumes comfort with Julia, local installation and computational modeling. Community support and documentation are the stated support channels rather than a managed service. Choose Kinetic.jl when particle transport, fluid equations, parallel computing or research experimentation are central requirements. Choose a broader general-purpose simulator when your work extends beyond these physics domains or calls for a more guided application experience.

Your product? Our editors can test Kinetic.jl in depth and publish a review, labelled as paid · from $149/mo →

Kinetic.jl pricing

Plans Free planFree Free to use — no paid tier required for the core job.
See plans on xiaotianbai.com

Kinetic.jl fact sheet

Free planYes
Paid fromFree
Delivery modeDesktop
Lesson libraryNo
Authoring toolsNo
Assessment toolsNo
3D visualsNo
Offline accessYes
Data exportNot verified
DeploymentSelf-hosted
PlatformsLinux, Windows, macOS
SupportCommunity, Docs
Built forSolo, Small business, Mid-market, Enterprise (editorial estimate)
Integrations5 integrations: Julia, CUDA, Python (kineticpy), DifferentialEquations.jl, Flux
PricingFree plan
Websitexiaotianbai.com
Facts checked24 Sep 2026

Kinetic.jl integrations

Kinetic.jl lists 5 integrations on its own site.

  • Julia
  • CUDA
  • Python (kineticpy)
  • DifferentialEquations.jl
  • Flux

Alternatives to Kinetic.jl

See all Kinetic.jl alternatives →

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Featured on iTechGuides

Featured on iTechGuides — Kinetic.jl 6.9/10

Kinetic.jl is listed in our Physics Simulation Software directory. Add the badge to your site — it links back to this page.

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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

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