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AI · alternatives · 2026

24 alternatives to Lumic

Decentralized gpu computing

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 1 we have checked on their own sites, 1 of them free or with a free tier.

  1. 1

    Hey we are Computable. We spent years building trading infrastructure at Jump Trading and Coinbase. From that point of view, compute looks like energy markets before 2000: everything trades through private bilateral leases, there’s no visible price, and nothing can be resold. The same H100 rents at a 2x spread depending on who’s asking, and once you sign a 24-month lease, it can never change hands. So we built a market for GPU nodes, sold by the calendar week. Here are three things you can do on it that you can’t do anywhere else: - Buy exactly the weeks you need. Three nodes for the last…

    Aug 2026 · getcomputable.com · its alternatives →

  2. 2

    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 →

  3. 3AG

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

    Apr 2026 · jaso1024.com · its alternatives →

  4. 4

    We developed a tool to trick your computer into thinking it’s attached to a GPU which actually sits across a network. This allows you to switch the number or type of GPUs you’re using with a single command.

    2024 · thundercompute.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. 6CG

    vEdge is a GPU cloud compute platform making computing affordable and accessible.

    2021 · gpu.land · its alternatives →

  7. 7

    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 →

  8. 8

    The easiest way to use cloud GPUs

    2025 · tensorpool.dev · its alternatives →

  9. 9
    Cerebrium▲300

    If you haven’t noticed, GPUs are scarce right now. The global boom in inference has demand growing faster than supply can keep up, and at Cerebrium ...

    2024 · cerebrium.ai · its alternatives →

  10. 10

    Easy to use and fairly priced GPUs for Machine Learning

    2019 · clevergrid.io · its alternatives →

  11. 11
    GPU.LAND▲126

    Affordable cloud GPUs for deep learning

    2021 · vedge.cloud · its alternatives →

  12. 12

    Hi HN, We just opened public access to Qwen3‑Coder‑480B‑A35B‑Instruct via a REST/SDK API. Why it might be interesting: - Fully open-source (Apache‑2.0): https://github.com/QwenLM/Qwen3-Coder - 480B params (35B active MoE), long context up to 1M tokens with YaRN - Matches Claude Sonnet/GPT‑4o on SWE-Bench Verified (81.6%) - Free tier: 100K tokens/month

    2023 · netmind.ai · its alternatives →

  13. 13

    Self-host AI/ML with the world's cheapest GPU cloud

    2025 · thundercompute.com · its alternatives →

  14. 14

    The world’s most powerful chip’ for AI

    2024 · nvidia.com · its alternatives →

  15. 15

    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 →

  16. 16

    An on-premises, bare-metal solution for deploying GPU-powered applications in containers - emergingstack/es-dev-stack

    2016 · github.com · its alternatives →

  17. 17
    NiceGPU▲13

    On-demand GPU power for AI and coding.

    2025 · nicegpu.com · its alternatives →

  18. 18

    Hi HN, I've been building Lukan, an open-source (MIT) agentic workstation that runs entirely as a single Rust binary with zero runtime dependencies. I started this because I wanted a unified workstation optimized for my own productivity. My goal was to build an environment where I could securely remote into my machine from anywhere, seamlessly view and modify local files, and run AI agents or drop into a terminal side-by-side, all integrated with a rich set of built-in tools. Here is what makes it different: Multi-agent sessions: Run multiple agents in parallel, each with its own isolated…

    Apr 2026 · lukan.ai · its alternatives →

  19. 19

    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 →

  20. 20
    Lunen.ai▲112

    Build AI agents your whole team can run, and control

    Jul 2026 · lunen.ai · its alternatives →

  21. 21BG
  22. 22

    dstack is a unified control plane for GPU provisioning and orchestration that works with any GPU cloud, Kubernetes, or on-prem clusters.

    2024 · dstack.ai · its alternatives →

  23. 23

    Ulixcode-labs/gpu-pro

    Nov 2025 · github.com · its alternatives →

  24. 24

    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 →

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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 →