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Products that do what Buildfunctions does

GPU Functions: Deploy AI Models & Run Serverless Inference

  1. 1

    AI models that run on an inference cloud optimized for speed

    May 2026 · generalcompute.com

  2. 2
    ZeroGPU309

    The compute efficient layer for AI inference

    Jun 2026 · zerogpu.ai

  3. 3
    RunInfra156

    Describe the AI model you need and get an optimized AI

    Jul 2026 · runinfra.ai

  4. 4
    Banana235

    Serverless GPUs for Machine Learning inference

    2022

  5. 5GA

    2021 · inferrd.com

  6. 6TC

    Hello HN! I’m Jonathan from TensorDock. After 7 months in beta, we’re finally launching Core Cloud, our platform to deploy GPU virtual machines in as little as 45 seconds! https://www.tensordock.com/product-core Why? Training machine learning workloads at large clouds can be extremely expensive. This left us wondering, “how did cloud ever become more expensive than on-prem?” I’ve seen too many ML startups buy their own hardware. Cheaper dedicated servers with NVIDIA GPUs are not too hard to find, but they lack the functionality and scalability of the big clouds. We thought to…

    2022 · tensordock.com

  7. 7

    Calculate the GPU memory you need for LLM inference

    2025

  8. 8

    The easiest way to use cloud GPUs

    2025

  9. 9

    Accelerate AI & ML with High-Performance GPU Servers

    Dec 2025 · vpsmalaysia.com.my

  10. 10

    The decentralised machine learning and AI platform

    2023

  11. 11
    GPU.LAND126

    Affordable cloud GPUs for deep learning

    2021

  12. 12

    Run AI jobs from your IDE with a one-click workflow

    Mar 2026 · oncompute.ai

  13. 13

    AI-Native Data Infrastructure for Spatial and Physical AI

    Apr 2026 · zibra.ai

  14. 14

    AI Journey Starts Here

    Sep 2025

  15. 15S1

    I wanted to build an inference provider for proprietary AI models, but I did not have a huge GPU farm. I started experimenting with Serverless AI inference, but found out that coldstarts were huge. I went deep into the research and put together an engine that loads large models from SSD to VRAM up to ten times faster than alternatives. It works with vLLM, and transformers, and more coming soon. With this project you can hot-swap entire large models (32B) on demand. Its great for: Serverless AI Inference Robotics On Prem deployments Local Agents And Its open source. Let me know if anyone…

    Nov 2025 · github.com

  16. 16

    The world’s most powerful chip’ for AI

    2024

  17. 17DO

    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

  18. 18DG
  19. 19BD
  20. 20

    AI Journey Starts Here

    Oct 2025 · cyfuture.ai

  21. 21PI

    Deploying vision models is time consuming and tedious. Setting up dependencies. Fixing conflicts. Configuring TRT acceleration. Flashing (and re-flashing) NVIDIA Jetsons. A streamlined, developer-friendly solution for inference is needed. We, the Roboflow team, have been hard at work open sourcing Inference, an open source vision deployment solution. Our solution is designed with developers in mind, offering a HTTP-based interface. Run models on your hardware without having to write architecture-specific inference code. Here's a demo showing how to go from a model to GPU inference on a video…

    2023 · github.com

  22. 22

    Pool compute to run powerful open models

    Apr 2026 · anarchai.org

  23. 23

    Deploy and scale GPU clusters instantly

    Oct 2025 · gmicloud.ai

  24. 24

    Unleash Extreme AI Performance with NVIDIA H100 GPU Server

    Oct 2025 · cyfuture.ai

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