Starcloud
Starcloud builds data centers in space utilizing 24/7 solar energy and radiative cooling to provide gigawatt-scale AI training infrastructure while avoiding terrestrial permitting constraints.
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Starcloud builds data centers in space utilizing 24/7 solar energy and radiative cooling to provide gigawatt-scale AI training infrastructure while avoiding terrestrial permitting constraints. Key capabilities include deploying Nvidia H100 GPUs for in-space computation, enabling the first training of LLMs and execution of models like Gemini in orbit. This solution targets organizations requiring massive computational power for AI development and satellite operations. Pricing details are not publicly listed and require direct inquiry.
Key features
- Space-based data centers with 24/7 solar energy
- GPU compute deployment for AI training and satellites
- Operation of Nvidia H100 in space for LLM training
- Radiative cooling to avoid terrestrial energy constraints
Pros & cons
Collected from user feedback found in web search
Pros
- Orbital data centers provide cooling efficiency and latency reduction
- Partnerships with NVIDIA demonstrate industry validation
- Principal engineer from SpaceX brings production experience
Cons
- Orbital deployment faces extreme technical challenges and costs
- Space launch dependencies create operational constraints
Pricing
Use cases
- Training Large Language Models (LLMs) in space
- Running AI models like Gemini in orbit
- Providing GPU compute resources to other satellites
Who it is for
AI researcherssatellite operators
Integrations
NVIDIAGoogle CloudCapella SpaceMission SpaceCrusoe Cloud
Tags
API
How we verified this
Company, pricing, and feature details come from the primary sources below and our latest verification pass. When sources disagree, the official source and the most recent check win.
Last verified 09/06/2026Verified sources: 1
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