Alternatives

Products that do what Cudair – live-reloading for developing CUDA applications does

cudair enable live-reloading for developing CUDA applications like golang-air.

1. 1
   Forge CLI▲107

   Swarm agents optimize CUDA/Triton for any HF/PyTorch model

   Jan 2026

2. 2
   RightNow CLI▲121

   Claude Code for CUDA, an open-source AI CLI for GPU devs

   Oct 2025

3. 3
   WoolyAI Acceleration Service▲100

   GPU service with GPU core and memory resources used billing

   2025

4. 4
   CUDA 13.1▲167

   The biggest CUDA expansion since 2006

   Dec 2025

5. 5
   Cursor▲210

   The AI Code Editor

   2024

6. 6
   Gouache▲77

   Enhance your design to production workflow

   2022

7. 7
   Forge Agent▲113

   Swarm Agents That Turn Slow PyTorch Into Fast GPU Kernels

   Jan 2026

8. 8
   Phion.dev▲158

   Build in Cursor like in Lovable - auto start, save & deploy

   2025

9. 9
   RunInfra▲156

   Describe the AI model you need and get an optimized AI

   Jul 2026 · runinfra.ai

10. 10
    Unveil Engine▲129

    Cursor for game developers

    2025

11. 11PA
    Parcel, a simple resource bundler for Golang▲26

    2018 · github.com

12. 12SC
    Shadergarden: Create reloadable graphical pipelines with Lisp and GLSL▲47

    2021 · blog.tonari.no

13. 13CP
    CUDA Pathtracer with Lots of Features▲10

    2020 · github.com

14. 14RP
    Run PyTorch locally with a remote GPU backend▲5

    I integrated a remote GPU execution backend into PyTorch through the same system that custom hardware accelerators get integrated into PyTorch. You can create a remote machine and obtain its CUDA device whenever you want to create or move tensors onto the remote GPU. machine = mycelya_torch.RemoteMachine("modal", "A100") cuda_device = machine.device("cuda") x = torch.randn(1000, 1000, device=cuda_device) y = torch.randn(1000, 1000).to(cuda_device) I made it reasonably performant by having most operations dispatch asynchronously whenever possible. For cases where slow performance is…

    Oct 2025 · github.com

15. 15GL
    Golang – Level 7 Load Balancer and Cache▲18

    2019 · github.com

16. 16LR
    Live Reloading WebGL Shaders▲20

    2017 · github.com

17. 17SL
    Simple Load Balancer – Golang▲16

    2018 · github.com

18. 18GS
    Gpu.st – GPU over SSH▲5

    Instantly create GPU instances over SSH. Instances boot a custom image with PyTorch, Jupyter, and the CUDA toolkit installed by default.

    Jan 2026 · gpu.st

19. 19AO
    A open source Heroku-like PaaS that runs on your server▲32

    2020 · repobus.com

20. 20GP
    GoCheese: Python private package repository and caching proxy▲30

    2019 · gocheese.cypherpunks.ru

21. 21GA
    Geeonx a Multiplatform C GUI-Library (Linux, Windows, macOS)▲23

    2019 · geeonx.org

22. 22
    Compute.cx is simple (modal.com like) interface for on-demand GPUs▲7

    Hi everyone, Please checkout compute.cx which is a simple cli interface for using on demand GPUs from RunPod and HotAisle. I created this because I really like the ease of modal.com for severless gpu access, but don’t always want to pay their markup. Compute.cx gives the same DX but on public on-demand GPUs like runpod and hotaisie. Please try it out, and write to me [email protected] for any questions/suggestions, or file a bug report on https://github.com/theoriclabs/docs.compute.cx Thanks! Harsh Gupta https://x.com/hargup13 P.S. BYOK AWS, GCP and…

    17d ago · compute.cx

23. 23RW
    Raytracer with both C++ and CUDA back ends▲5

    2021 · github.com

24. 24GT
    Golang Throttler – smart WaitGroups to easily manage worker goroutines▲5

    2015 · github.com

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