Independent comparison Updated April 2026 20 GPU providers tested Real hourly pricing

GPU cloud comparison · 2026

H

Hyperstack vs Paperspace

Hyperstack wins on 5 of 5 key metrics — but the right choice depends on your workload.

Overall Winner
H
Hyperstack
Global GPU cloud specialist — H100, A100 80GB and L40 from $0.11/h
from $0.11/h
★★★★☆ 4.3 / 5 (198 reviews)
Try Hyperstack →
VS
Paperspace
Gradient notebooks + GPU VMs — great for ML teams
from $0.45/h
★★★★☆ 4.3 / 5 (1,456 reviews)
Try Paperspace →

Head-to-Head Comparison

H Hyperstack
Paperspace
Starting Price Lower hourly rate
from $0.11/h
from $0.45/h
Overall Rating User rating
4.3 / 5
4.3 / 5
GPU Types Variety
5 types
4 types
Max VRAM Largest available
80 GB
80 GB
Locations Regions covered
UK, EU
US, EU
Wins out of 5
5
0

GPU Availability

H Hyperstack
RTX A6000A100 80GBH100L40L40S

VRAM: 48–80 GB · Locations: UK, EU

Paperspace
A100A6000RTX 4000V100

VRAM: 8–80 GB · Locations: US, EU

Pros & Cons

H Hyperstack
Pros
  • Outstanding entry pricing for A6000
  • Full networking stack (VPC, firewall, NAT)
  • UK / EU regions for European latency
  • Reservation discount up to 75%
Cons
  • No B200 / H200 yet (April 2026)
  • Smaller marketing footprint than RunPod
  • Limited template marketplace
Paperspace
Pros
  • Best notebook experience of any cloud GPU
  • Team collaboration features built-in
  • Free tier with limited GPU hours
  • Good documentation and tutorials
Cons
  • Pricier than RunPod for raw compute
  • Limited GPU types vs competitors
  • Gradient platform has occasional issues

Which Should You Choose?

H Choose Hyperstack if…
  • You need GPU compute for Budget training jobs
  • You need GPU compute for Stable Diffusion at scale
  • You need GPU compute for VPC-isolated workloads
  • You need GPU compute for EU-friendly compute
  • Lower price is your top priority (from $0.11/h vs from $0.45/h)
  • Higher user satisfaction matters (4.3 vs 4.3)
  • You want more GPU variety (5 vs 4 types)
Choose Paperspace if…
  • You need GPU compute for Notebooks
  • You need GPU compute for ML teams
  • You need GPU compute for Prototyping
  • You need GPU compute for Education