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Life & fun · alternatives · 2026

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24 alternatives to Cloud GPUs for Deep Learning – At 1/3 the Cost of AWS/GCP

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

GPU.land offers cloud GPU access for deep learning projects at significantly lower pricing than major providers like AWS and GCP. The service targets machine learning engineers and researchers who need scalable… 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. Cloud GPUs for Deep Learning – At 1/3 the Cost of AWS/GCP launched in 2021; newer entries below may have overtaken it.

  1. 1
    GPU.LAND▲126

    Affordable cloud GPUs for deep learning

    2021 · vedge.cloud · its alternatives →

  2. 2TC

    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 · its alternatives →

  3. 3

    Deep Learning Everywhere, For Everyone

    2017 · nvidia.com · its alternatives →

  4. 4

    Greetings HN! This is Doruk from Oblivus, and I'm excited to announce the launch of our platform, Oblivus Cloud. After more than a year of beta testing, we're excited to offer you a platform where you can deploy affordable and scalable GPU virtual machines in as little as 30 seconds! https://oblivus.com/cloud - What sets Oblivus Cloud apart? At the start of our journey, we had two primary goals in mind: to democratize High-Performance Computing and make it as straightforward as possible. We understand that maintaining GPU servers through major cloud service providers can be…

    2023 · oblivus.com · its alternatives →

  5. 5

    AI models that run on an inference cloud optimized for speed

    May 2026 · generalcompute.com · its alternatives →

  6. 6
    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 →

  7. 7

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

    2016 · github.com · its alternatives →

  8. 8SS

    Running DeepSeek V3 (685B) requires 8×H100 GPUs which is about $14k/month. Most developers only need 15-25 tok/s. sllm lets you join a cohort of developers sharing a dedicated node. You reserve a spot with your card, and nobody is charged until the cohort fills. Prices start at $5/mo for smaller models. The LLMs are completely private (we don't log any traffic). The API is OpenAI-compatible (we run vLLM), so you just swap the base URL. Currently offering a few models.

    Apr 2026 · sllm.cloud · its alternatives →

  9. 9

    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 →

  10. 10

    The easiest way to use cloud GPUs

    2025 · tensorpool.dev · its alternatives →

  11. 11

    Compare GPU rental prices across cloud providers

    7d ago · gpu.context.dev · its alternatives →

  12. 12
    ZeroGPU▲298

    The compute efficient layer for AI inference

    Jun 2026 · zerogpu.ai · its alternatives →

  13. 13

    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 →

  14. 14

    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 →

  15. 15

    Multi-GPU reinforcement learning using Deep Q-Network in TensorFlow for OpenAI Gym - vishar0/dist-dqn

    2016 · github.com · its alternatives →

  16. 16TG

    Hey folks! I’m Jonathan from TensorDock, and we’re building a cloud GPU marketplace. We want to make GPUs truly affordable and accessible. I once started a web hosting service on self-hosted servers in middle school. But building servers isn’t the same as selling cloud. There’s a lot of open source software to manage your homelab for side projects, but there isn’t anything to commercialize that. Large cloud providers charge obscene prices — so much so that they can often pay back their hardware in under 6 months with 24x7 utilization. We are building the software that allows anyone to become…

    2024 · dashboard.tensordock.com · its alternatives →

  17. 17IM
  18. 18

    TensorFlow for AWS. Contribute to dsys/tensorflow development by creating an account on GitHub.

    2015 · github.com · its alternatives →

  19. 19

    ML dev tool that saves you up to 8x in cloud GPU costs

    2019 · its alternatives →

  20. 20

    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 →

  21. 21

    Affordable H100, H200, GB300, and B200 GPU compute for training, inference, and everything in between.

    Sep 2026 · compute.cheap · its alternatives →

  22. 22

    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 →

  23. 23GA
  24. 24

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

    2025 · thundercompute.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 →