GPU cloud comparison · 2026
AWS GPU (EC2) vs Jarvis Labs
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
Jarvis Labs
On-demand H100 / A100 / RTX 6000 Ada from $0.39/h
from $0.39/h
★★★★☆ 4.3 / 5 (312 reviews)
Try Jarvis Labs →Head-to-Head Comparison
AWS GPU (EC2)
Jarvis Labs
Starting Price Lower hourly rate
from $3.06/h
from $0.39/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, Asia
Wins out of 5
3
2
GPU Availability
AWS GPU (EC2)
A100H100V100T4Inferentia2
VRAM: 16–80 GB · Locations: US, EU, APAC, Global
Jarvis Labs
RTX 6000 AdaA100 40GBA100 80GBH100
VRAM: 48–80 GB · Locations: US, Asia
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
Jarvis Labs
Pros
- Excellent pricing for H100
- RTX 6000 Ada — 48GB at moderate cost
- Polished UI for non-DevOps users
- Quick spinup, low friction
Cons
- Smaller GPU variety than RunPod
- No serverless / autoscaling
- Limited European presence
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 Jarvis Labs if…
- You need GPU compute for Researchers and indie developers
- You need GPU compute for Llama fine-tuning
- You need GPU compute for Stable Diffusion training
- You need GPU compute for Jupyter notebook users
- Lower price is your top priority (from $0.39/h vs from $3.06/h)
- Higher user satisfaction matters (4.3 vs 4.2)