GPU cloud comparison · 2026
Hyperstack vs Lambda Labs
Hyperstack wins on 4 of 5 key metrics — but the right choice depends on your workload.
Overall Winner
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
Lambda Labs
On-demand H100 clusters — developer-favourite for serious ML
from $1.10/h
★★★★★ 4.5 / 5 (1,872 reviews)
Try Lambda Labs →Head-to-Head Comparison
Hyperstack
Lambda Labs
Starting Price Lower hourly rate
from $0.11/h
from $1.10/h
Overall Rating User rating
4.3 / 5
4.5 / 5
GPU Types Variety
5 types
4 types
Max VRAM Largest available
80 GB
80 GB
Locations Regions covered
UK, EU
US, AU
Wins out of 5
4
1
GPU Availability
Hyperstack
RTX A6000A100 80GBH100L40L40S
VRAM: 48–80 GB · Locations: UK, EU
Lambda Labs
A100 40GBA100 80GBH100A10
VRAM: 24–80 GB · Locations: US, AU
Pros & Cons
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
Lambda Labs
Pros
- Reliable on-demand H100 availability
- No complex setup — SSH ready in seconds
- Lambda Stack saves setup time
- Competitive pricing vs hyperscalers
Cons
- Limited GPU types vs RunPod
- Fewer EU datacenter options
- No serverless endpoints
Which Should You Choose?
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 $1.10/h)
- You want more GPU variety (5 vs 4 types)
Choose Lambda Labs if…
- You need GPU compute for LLM training
- You need GPU compute for Research
- You need GPU compute for Fine-tuning
- You need GPU compute for Multi-GPU jobs
- Higher user satisfaction matters (4.5 vs 4.3)