Alternatives

Products that do what Medjed AI does

Fast, Scalable GPU Cloud for AI.

1. 1CG
   Cloud GPUs for Deep Learning – At 1/3 the Cost of AWS/GCP▲168

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2. 2
   Tensorflow Research Cloud▲288

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3. 3
   CloudMedx▲93

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4. 4
   OpenAI Universe▲329

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5. 5
   Paperspace for Machine Learning▲152

   A Linux desktop in the cloud built for Machine Learning

   2016

6. 6DG
   Dockerized GPU Deep Learning Solution (Code and Blog and TensorFlow Demo)▲80

   2016 · github.com

7. 7
   Nvidia Blackwell B200 GPU▲146

   The world’s most powerful chip’ for AI

   2024

8. 8VA
   Vector - A High-Level Programming Language for GPU Computing▲142

   2013 · zhehaomao.com

9. 9
   TensorFire▲99

   Blazing-fast in-browser neural networks

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10. 10
    Thunder Compute (YC S24)▲116

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

    2025

11. 11AP
    AI Planning for Starcraft▲78

    2015 · github.com

12. 12GB
    GPU-backed Linux desktops in the cloud▲23

    2016 · paperspace.com

13. 13AL
    A Language for Programming GPUs▲12

    2019 · dev.to

14. 14
    Rent GPU Server▲6

    AI Journey Starts Here

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15. 15
    GMI Cloud▲12

    Deploy and scale GPU clusters instantly

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16. 16
    NVIDIA H100 GPU SERVER▲12

    Unleash Extreme AI Performance with NVIDIA H100 GPU Server

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17. 17QS
    Quickly search, build and share AI models▲19

    2020 · picsellia.com

18. 18IA
    InfiniteGPU, An open-source AI compute network,now supporting training▲5

    Jan 2026 · github.com

19. 195L
    50+ LLMs on 2 GPUs with 2-Second Swapping? We built AI-Native Runtime▲5

    We've built InferX, a specialized runtime environment that fundamentally changes how LLMs are served. The core problem we solve is the latency bottleneck in AI inference, especially with large models. Current systems waste resources or suffer from painfully slow cold starts. InferX's AI-native architecture, with its "snapshot" technology, enables: * *Sub-2s cold starts:* Spin up models instantly. * *High density:* Serve more LLMs on the same GPUs. * *Optimal efficiency:* Maximize GPU utilization. This isn't just another API; it's a new execution layer designed from the ground up for the…

    2025 · github.com

20. 20
    Aqaba AI▲6

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21. 21
    hosted·ai▲3

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    5d ago · hosted.ai

22. 22OJ
    Oceananigans.jl: A fast ocean model in Julia that runs on CPUs and GPUs▲16

    2019 · github.com

23. 23
    GPU as a Service▲11

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24. 24OS
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