AI Training
Real machines. Renewable power. Running in Australia.
Live across Australia
Public workloads running on available renewable-powered machines.
Australian-founded technology company developing a transparent, decentralized computing network powered by renewable energy.© 2026 Solar Compute Limited
Latest training runs
Completed public AI training workloads and their metrics.
What happens next
Every training workload moves through the same controlled network process.
Submit
The training workload is submitted through the public launcher.
Validate
The request is checked against public workload rules.
Queue
The workload is queued for an available machine.
Run
The workload runs under limits and returns a status or result.
About this workload
AI training workloads are used for fine-tuning, small training runs, dataset validation and testing.
These workloads help validate machine allocation, runtime controls, queue handling and result delivery across the SolarCompute network.
Supported public tests
- Fine-tuning tests
- Dataset validation
- Small training runs
- Model evaluation
- Research workloads
Run your first training job
Submit a public training workload, or explore what the network has already run.