GPU cloud comparison · 2026
Crusoe vs Google Cloud GPU
Crusoe wins on 4 of 5 key metrics — but the right choice depends on your workload.
Overall Winner
Crusoe
Climate-aligned GPU cloud — H100, H200, B200 and MI300X on green energy
from $0.40/h
★★★★☆ 4.4 / 5 (412 reviews)
Try Crusoe →VS
Google Cloud GPU
TPU + GPU powerhouse — best ecosystem for TensorFlow
from $2.48/h
★★★★☆ 4.3 / 5 (2,891 reviews)
Try Google Cloud GPU →Head-to-Head Comparison
Crusoe
Google Cloud GPU
Starting Price Lower hourly rate
from $0.40/h
from $2.48/h
Overall Rating User rating
4.4 / 5
4.3 / 5
GPU Types Variety
6 types
5 types
Max VRAM Largest available
192 GB
80 GB
Locations Regions covered
US, Iceland
US, EU, APAC, Global
Wins out of 5
4
1
GPU Availability
Crusoe
H100H200B200A100 80GBL40SMI300X
VRAM: 48–192 GB · Locations: US, Iceland
Google Cloud GPU
A100 40GBA100 80GBH100T4V100
VRAM: 16–80 GB · Locations: US, EU, APAC, Global
Pros & Cons
Crusoe
Pros
- Among the cheapest H200 access — from $2.10/h
- B200 availability while most clouds wait-list
- InfiniBand 3.2 Tb interconnects for serious multi-node
- Climate-positive operations (uses flared methane)
Cons
- Smaller GPU variety than RunPod
- Region selection limited (mostly US + Iceland)
- Sales-led for large deployments
Google Cloud GPU
Pros
- Best TPU availability for TF workloads
- Deep Vertex AI + BigQuery integration
- Global infrastructure and reliability
- Preemptible instances cut costs significantly
Cons
- Expensive on-demand pricing
- Complex billing — easy to overspend
- Steep learning curve for GCP newcomers
Which Should You Choose?
Choose Crusoe if…
- You need GPU compute for LLM training at scale
- You need GPU compute for Multi-node H100/H200 jobs
- You need GPU compute for Sustainable AI workloads
- You need GPU compute for AMD MI300X clusters
- Lower price is your top priority (from $0.40/h vs from $2.48/h)
- Higher user satisfaction matters (4.4 vs 4.3)
- You want more GPU variety (6 vs 5 types)
Choose Google Cloud GPU if…
- You need GPU compute for TensorFlow workloads
- You need GPU compute for TPU training
- You need GPU compute for Enterprise AI
- You need GPU compute for Vertex AI pipelines