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

GPU cloud comparison · 2026

C

Crusoe vs Salad

S

Crusoe wins on 4 of 5 key metrics — but the right choice depends on your workload.

Overall Winner
C
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
S
Salad
Distributed inference cloud — RTX 3090/4090 from $0.03/h
from $0.03/h
★★★★☆ 3.9 / 5 (423 reviews)
Try Salad →

Head-to-Head Comparison

C Crusoe
S Salad
Starting Price Lower hourly rate
from $0.40/h
from $0.03/h
Overall Rating User rating
4.4 / 5
3.9 / 5
GPU Types Variety
6 types
4 types
Max VRAM Largest available
192 GB
24 GB
Locations Regions covered
US, Iceland
Global (distributed)
Wins out of 5
4
1

GPU Availability

C Crusoe
H100H200B200A100 80GBL40SMI300X

VRAM: 48–192 GB · Locations: US, Iceland

S Salad
RTX 3090RTX 4090RTX 3080RTX 3070

VRAM: 8–24 GB · Locations: Global (distributed)

Pros & Cons

C 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
S Salad
Pros
  • Absurdly cheap — RTX 3090 from $0.03/h
  • Massive horizontal scale (1000+ nodes)
  • Auto-fleet management for inference
  • No data-egress charges
Cons
  • Distributed = no persistent storage
  • Not suitable for training
  • Latency varies by node geography

Which Should You Choose?

C 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
  • Higher user satisfaction matters (4.4 vs 3.9)
  • You want more GPU variety (6 vs 4 types)
S Choose Salad if…
  • You need GPU compute for Stateless inference
  • You need GPU compute for Stable Diffusion bulk generation
  • You need GPU compute for Embedding generation
  • You need GPU compute for Cost-sensitive batch jobs
  • Lower price is your top priority (from $0.03/h vs from $0.40/h)