GPU cloud comparison · 2026
Paperspace vs Together AI
Paperspace wins on 3 of 5 key metrics — but the right choice depends on your workload.
Overall Winner
Paperspace
Gradient notebooks + GPU VMs — great for ML teams
from $0.45/h
★★★★☆ 4.3 / 5 (1,456 reviews)
Try Paperspace →VS
Together AI
Inference-first GPU cloud — H100/H200 with optimized serving stacks
from $1.49/h
★★★★☆ 4.4 / 5 (521 reviews)
Try Together AI →Head-to-Head Comparison
Paperspace
Together AI
Starting Price Lower hourly rate
from $0.45/h
from $1.49/h
Overall Rating User rating
4.3 / 5
4.4 / 5
GPU Types Variety
4 types
4 types
Max VRAM Largest available
80 GB
141 GB
Locations Regions covered
US, EU
US, EU
Wins out of 5
3
2
GPU Availability
Paperspace
A100A6000RTX 4000V100
VRAM: 8–80 GB · Locations: US, EU
Together AI
H100H200A100 80GBL40S
VRAM: 48–141 GB · Locations: US, EU
Pros & Cons
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
Together AI
Pros
- Best-in-class inference performance
- Excellent open-source model coverage
- Strong fine-tuning workflow
- Token-based pricing for variable load
Cons
- Less GPU variety than RunPod
- Focus is inference, not raw training
- Custom interconnects not exposed
Which Should You Choose?
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 $1.49/h)
- You want more GPU variety (4 vs 4 types)
Choose Together AI if…
- You need GPU compute for High-throughput inference
- You need GPU compute for Open-source LLM serving
- You need GPU compute for Llama / Mistral fine-tuning
- You need GPU compute for Production AI APIs
- Higher user satisfaction matters (4.4 vs 4.3)