GPU cloud comparison · 2026
CoreWeave vs Together AI
Together AI wins on 3 of 5 key metrics — but the right choice depends on your workload.
CoreWeave
Enterprise H100 clusters — Kubernetes-native GPU cloud
from $2.06/h
★★★★☆ 4.4 / 5 (412 reviews)
Try CoreWeave →VS
Overall Winner
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
CoreWeave
Together AI
Starting Price Lower hourly rate
from $2.06/h
from $1.49/h
Overall Rating User rating
4.4 / 5
4.4 / 5
GPU Types Variety
3 types
4 types
Max VRAM Largest available
80 GB
141 GB
Locations Regions covered
US, EU
US, EU
Wins out of 5
2
3
GPU Availability
CoreWeave
H100 SXMA100 SXMA40
VRAM: 40–80 GB · Locations: US, EU
Together AI
H100H200A100 80GBL40S
VRAM: 48–141 GB · Locations: US, EU
Pros & Cons
CoreWeave
Pros
- Best multi-node GPU cluster performance
- High-speed InfiniBand interconnects
- Purpose-built for AI workloads
- Strong enterprise support
Cons
- Expensive — not for hobbyists
- Requires Kubernetes knowledge
- Sales-led process for large clusters
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 CoreWeave if…
- You need GPU compute for Large-scale training
- You need GPU compute for Foundation models
- You need GPU compute for Enterprise AI
- You need GPU compute for Multi-node jobs
- Higher user satisfaction matters (4.4 vs 4.4)
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
- Lower price is your top priority (from $1.49/h vs from $2.06/h)
- You want more GPU variety (4 vs 3 types)