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work with large models,
free from computational constraints.

join waitlist

for developers &
providers.

kluster.ai empowers developers to run and tune large AI models on a distributed compute grid sourced by GPU providers from all around the globe.

  • Code
    response = klusterai.infer(
  model = "",
  prompt = ""
)

print(response)
    Output
    developers

    Seamlessly access the performance and accuracy you need without the hassle of GPU management.  

  • providers

    Join the distributed global grid with rapid onboarding/offboarding for optimal hardware utilization.

how it works.

kluster.ai abstracts the complexity of running AI on a distributed network with the use of our Adaptive Pipelines technology. This enables large models to run efficiently across a network of heterogeneous hardware, streamlining performance, ensuring scalability, and optimizing resource utilization.

  • tensor fragments

    We pack AI models so they can run on many different GPUs, using resources more efficiently.

  • selective activation

    We analyze your request and activate only the fragments that are essential for the result.

  • compute scheduler

    We determine the best sequence of GPUs to ensure stable and reliable performance each time.

learn more.

Join our waitlist to stay informed about the latest advancements with kluster.ai’s distributed GPU network.