What Thunder Compute is
Thunder Compute is GPU infrastructure rather than a model service. It offers persistent GPU instances that you connect to, plus programmatic microVM sandboxes for agent workloads, on A100 and H100 hardware, with billing measured in fine time increments and launch paths from either a terminal or an agent.
What you can do with it
- Launch a GPU instance from the terminal
- Create sandboxes programmatically for agents
- Snapshot instances when work finishes
- Run training or serving jobs on demand
- Compare cost against larger clouds
Who it is for
- AI startups and researchers
- Data scientists needing short GPU access
- Teams running agent workloads that need GPUs
What to watch out for
- Cost comparisons against major clouds are vendor claims; measure on your own jobs
- You are responsible for everything you store and run on rented hardware, including data wiping afterwards
- Sandboxes executing untrusted agent code need isolation, timeouts and spend caps
- Availability of specific GPU types fluctuates with demand
Pros & cons
✓ What we like
- Fine-grained billing rather than hourly blocks
- Both instances and sandboxes offered
- Terminal-first workflow
! What to watch out for
- Cost claims need verification
- Your responsibility for data on rented GPUs
- GPU availability fluctuates
FAQ
What hardware is available?
A100 and H100 instances are described, along with sandboxes for agent workloads.
How is billing measured?
Per-second and per-minute billing is described, with no long-term contracts.
What should I manage?
Data left on instances, isolation for sandboxes and spend limits for agents.
Last reviewed: 2026-09-19
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