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Dev tools · alternatives · 2026

24 alternatives to GPU-pro

Ulixcode-labs/gpu-pro

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.

  1. 1
    RightNow▲197

    AI code editor for GPU kernel development

    Dec 2025 · its alternatives →

  2. 2AG

    Thought the resources for GPU arch were lacking, so here we are

    Apr 2026 · jaso1024.com · its alternatives →

  3. 3

    The standard GPU utilization metric reported by nvidia-smi, nvtop, Weights & Biases, Amazon CloudWatch, Google Cloud Monitoring, and Azure Monitor is highly misleading. It reports the fraction of time that any kernel is running on the GPU, which means a GPU can report 100% utilization even if only a small portion of its compute capacity is actually being used. In practice, we've seen workloads with ~1–10% real compute throughput while dashboards show 100%. This becomes a problem when teams rely on that metric for capacity planning or optimization decisions, it can make underutilized systems…

    Apr 2026 · systalyze.com · its alternatives →

  4. 4

    On-GPU AI, built for the game

    2025 · nvidia.com · its alternatives →

  5. 5

    Insights on GPU and AI infrastructure from Arc Compute. Read hardware deep-dives, deployment playbooks, and analysis of where the AI compute market is heading.

    2021 · arccompute.com · its alternatives →

  6. 6GA
  7. 7

    The world’s most powerful chip’ for AI

    2024 · nvidia.com · its alternatives →

  8. 8

    Hi HN, I’m Joe. My friends Matthew, Jake and I are building Luminal (https://luminalai.com/), a GPU compiler for automatically generating fast GPU kernels for AI models. It uses search-based compilation to achieve high performance. We take high level model code, like you'd have in PyTorch, and generate very fast GPU code. We do that without using LLMs or AI - rather, we pose it as a search problem. Our compiler builds a search space, generates millions of possible kernels, and then searches through it to minimize runtime. You can try out a demo in `demos/matmul` on mac to…

    2025 · github.com · its alternatives →

  9. 9

    We built installable software for Windows & Linux that makes any remote Nvidia GPU accessible to, and shareable across, any number of remote clients running local applications, all over standard networking.

    2022 · github.com · its alternatives →

  10. 10

    I locked in for 18 hours and built Claude Code for CUDA. It is completely open source! It writes CUDA kernels, debugs memory issues, and optimizes for your specific GPU. It is a fully agentic AI with tool calling built specifically for the CUDA toolkit This is the CLI version of RightNow AI code editor, our GPU-native code editor with a built-in emulator, visual profiling, and remote GPU access. The CLI is open source, lightweight, and fast. It is designed for anyone who wants AI help with CUDA without setup I used Python because it is the most common language, so anyone can build on top of…

    2025 · github.com · its alternatives →

  11. 11

    Supercharge gaming with DLSS 4, NVIDIA Studio, and AI

    2025 · nvidia.com · its alternatives →

  12. 12VA
  13. 13

    GPU Observability with workload attribution. One OTLP agent per node ties hardware metrics (NVIDIA, AMD, Intel Gaudi) to the K8s pod or Slurm job burning the GPU. - last9/gpu-telemetry

    Jul 2026 · github.com · its alternatives →

  14. 14

    Real-time GPU shader editor for spatial computing

    2024 · shader.vision · its alternatives →

  15. 15

    Neurox control helm chart details. Contribute to neuroxhq/helm-chart-neurox-control development by creating an account on GitHub.

    2025 · github.com · its alternatives →

  16. 16

    Hi HN, we are Ed, Zach, and Ronald, creators of Shadeform (https://www.shadeform.ai/), a GPU marketplace to see live availability and prices across the GPU market, as well as to deploy and reserve on-demand instances. We have aggregated 8+ GPU providers into a single platform and API, so you can easily provision instances like A100s and H100s where they are available. From our experience working at AWS and Azure, we believe that cloud could evolve from all-encompassing hyperscalers (AWS, Azure, GCP) to specialized clouds for high-performance use cases. After the launch of…

    2023 · shadeform.ai · its alternatives →

  17. 17

    Deep Learning Everywhere, For Everyone

    2017 · nvidia.com · its alternatives →

  18. 18

    NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

    2016 · octo.ai · its alternatives →

  19. 19

    GPU Raytracer from scratch in C++/CUDA. Contribute to jan-van-bergen/GPU-Raytracer development by creating an account on GitHub.

    2021 · github.com · its alternatives →

  20. 20
    GPU.LAND▲126

    Affordable cloud GPUs for deep learning

    2021 · vedge.cloud · its alternatives →

  21. 21
    EVOLVE▲22

    Gpu ray-tracing benchmark

    2025 · evolvebenchmark.com · its alternatives →

  22. 22

    Most powerful GeForce GPU ever made

    2025 · nvidia.com · its alternatives →

  23. 23

    Compare GPU rental prices across cloud providers

    6d ago · gpu.context.dev · its alternatives →

  24. 24

    Demo of agent based model on GPU with CUDA and OpenGL (Windows/Linux) Agent instances on GPU memory Uses SSBO for instanced objects (with GLSL 450 shaders) CUDA OpenGL interops Renders with GLFW3 window manager Dynamic camera views in OpenGL (pan,zoom with mouse) Libraries installed using vcpkg (https://github.com/KienTTran/ABMGPU)

    2023 · github.com · its alternatives →

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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →