GPU cloud comparison · 2026
AWS GPU (EC2) vs Paperspace
AWS GPU (EC2) wins on 3 of 5 key metrics — but the right choice depends on your workload.
Overall Winner
AWS GPU (EC2)
Largest GPU fleet worldwide — P4/P5 instances for enterprise
from $3.06/h
★★★★☆ 4.2 / 5 (4,123 reviews)
Try AWS GPU (EC2) →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
AWS GPU (EC2)
Paperspace
Starting Price Lower hourly rate
from $3.06/h
from $0.45/h
Overall Rating User rating
4.2 / 5
4.3 / 5
GPU Types Variety
5 types
4 types
Max VRAM Largest available
80 GB
80 GB
Locations Regions covered
US, EU, APAC, Global
US, EU
Wins out of 5
3
2
GPU Availability
AWS GPU (EC2)
A100H100V100T4Inferentia2
VRAM: 16–80 GB · Locations: US, EU, APAC, Global
Paperspace
A100A6000RTX 4000V100
VRAM: 8–80 GB · Locations: US, EU
Pros & Cons
AWS GPU (EC2)
Pros
- Most comprehensive ML toolchain (SageMaker)
- Spot instances for massive cost savings
- Best compliance certifications globally
- Inferentia for cost-effective inference
Cons
- Most expensive on-demand GPU pricing
- Complex pricing model
- Not beginner-friendly for pure GPU rental
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?
Choose AWS GPU (EC2) if…
- You need GPU compute for Enterprise MLOps
- You need GPU compute for SageMaker pipelines
- You need GPU compute for Production inference
- You need GPU compute for Regulated industries
- 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
- Lower price is your top priority (from $0.45/h vs from $3.06/h)
- Higher user satisfaction matters (4.3 vs 4.2)