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

GPU cloud comparison · 2026

H

Hyperstack vs RunPod

R

Hyperstack wins on 3 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
R
RunPod
Best value GPU cloud — huge selection, community + secure cloud
from $0.20/h
★★★★★ 4.6 / 5 (3,241 reviews)
Try RunPod →

Head-to-Head Comparison

H Hyperstack
R RunPod
Starting Price Lower hourly rate
from $0.11/h
from $0.20/h
Overall Rating User rating
4.3 / 5
4.6 / 5
GPU Types Variety
5 types
5 types
Max VRAM Largest available
80 GB
80 GB
Locations Regions covered
UK, EU
US, EU, CA
Wins out of 5
3
2

GPU Availability

H Hyperstack
RTX A6000A100 80GBH100L40L40S

VRAM: 48–80 GB · Locations: UK, EU

R RunPod
RTX 3090RTX 4090A100 80GBH100A40

VRAM: 24–80 GB · Locations: US, EU, CA

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
R RunPod
Pros
  • Cheapest community GPUs from $0.20/h
  • Massive GPU variety including H100
  • Serverless endpoints for inference APIs
  • Great UI and pod management
Cons
  • Community cloud less reliable than dedicated
  • Storage costs add up over time
  • Support can be slow on free tier

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 $0.20/h)
  • You want more GPU variety (5 vs 5 types)
R Choose RunPod if…
  • You need GPU compute for Fine-tuning LLMs
  • You need GPU compute for Stable Diffusion
  • You need GPU compute for Training
  • You need GPU compute for Inference
  • Higher user satisfaction matters (4.6 vs 4.3)