fal.ai vs Spheron

Production endpoints for image, video and audio models billed by output unit (per image, per megapixel, per second or per video)

Run private models on dedicated NVIDIA GPUs with autoscaling and scale-to-zero

Inference engines tuned for diffusion and audio workloads

Access GPU capacity from multiple cloud providers and certified data centers from one account, without separate signups per provider

Instances are billed by the minute rather than rounded up to the hour, past a 20-minute minimum runtime (60 minutes for a 2x AMD MI300X)

NVIDIA instances are typically ready in under two minutes with no approval workflow or provisioning queue

Compute spend across every connected provider is tracked in a single dashboard

Each VM or bare metal instance includes NVMe SSD storage, network bandwidth and full root access, with a dedicated IP on NVIDIA instances

Spheron sources large clusters, specific hardware and InfiniBand configurations from its partner data center network, with a typical quote turnaround of 24-48 hours