Resource Tiers
A resource tier determines how much RAM and CPU an execution pod gets — and therefore how fast a run completes and how many credits it burns. You pick a tier each time you run a workflow, bounded by the maximum your subscription allows.
Compute sizes
| Size | RAM | CPU | Credits/sec | Credits/hour | Good for |
|---|---|---|---|---|---|
| Micro | 4 GB | 1 | 0.02 | 72 | Tiny tests, scripting nodes |
| Small | 16 GB | 2 | 0.08 | 288 | QC, bacterial genomes |
| Medium | 64 GB | 8 | 0.32 | 1,152 | Human WES, RNA-seq |
| Large | 128 GB | 16 | 0.64 | 2,304 | Human WGS, STAR, Cell Ranger |
| XLarge | 256 GB | 32 | 1.28 | 4,608 | Large assemblies |
| Extreme | 1 TB | 64 | 5.12 | 18,432 | Huge eukaryotic assemblies |
Subscription caps
Your plan caps the largest size you can run and how long a single job may run:
| Tier | Max RAM | Max runtime/job | Concurrent jobs | Storage |
|---|---|---|---|---|
| Free | 16 GB | 1 hour | 1 | 5 GB |
| Starter | 64 GB | 8 hours | 2 | 50 GB |
| Professional | 128 GB | 24 hours | 5 | 250 GB |
| Team | 256 GB | 72 hours | 10 | 1 TB |
| Enterprise | up to 4 TB | up to 7 days | Custom | Unlimited |
Choosing a tier
- Match RAM to the bottleneck node. Alignment and assembly nodes are usually the memory ceiling; pick a size that comfortably fits the largest step.
- Bigger isn’t always pricier per job. A larger instance finishes faster; since billing is per-second, a 2× faster run on a 2× costlier instance is roughly cost-neutral — but with less wall-clock time.
- Test small, run big. Validate a graph on a subset at Small, then run the full dataset at Large/XLarge.
Priority queue
Professional and above get priority queue placement, so runs start sooner during periods of high demand.