Choose GPU for accelerated ML and parallel workloads, or CPU for large-batch and general-purpose compute. Use the buttons below to open your email client with a tailored prefilled request.
Request GPU Quote Request CPU Quote
| Attribute | GPU instances | CPU instances |
|---|---|---|
| Best for | Parallel accelerated workloads (ML training, inference, video processing) | Batch processing, ETL, simulations, general-purpose services |
| Typical resources requested | GPUs (1+), 8–64 CPU cores, 32–512 GB RAM | Many CPU cores (8–256), moderate RAM (16–512 GB), high I/O |
| Scheduling tolerance | Lower — suited to short bursts and low-latency batches | Higher — suited to queued, long-running, or fault-tolerant jobs |
| Cost drivers | GPU availability and memory bandwidth | Core-hours and sustained CPU time |
| When to choose | Training/fine-tuning models, high-throughput inference, SIMD workloads | Data preprocessing, large-scale batch analytics, rendering where GPUs not required |
Tip: include the downloadable quote template to speed assessment: Download quote template. For developer onboarding and API access see Developer Quickstart.
See also: Detailed GPU vs CPU guidance Machines and specs Developer quickstart
Contact sales: hello@solarcompute.net.au