Provider Overview
Strengths & Best For
CoreWeave is a purpose-built GPU cloud offering H100 SXM5, H200, and A100 clusters with InfiniBand and NVLink interconnects for large-scale AI training and LLM fine-tuning. On-demand and reserved H100 instances are available across US East, US West, and EU regions, with some of the highest GPU density and lowest latency networking of any specialist cloud. A top choice for AI labs and enterprises running multi-node distributed training at scale.
- Highest GPU density
- InfiniBand networking
- Kubernetes-native
- Fast provisioning
Shadeform is a GPU cloud aggregator that provisions H100, A100, RTX 4090, and many other GPU types across 30+ underlying cloud providers through a single unified API, automatically routing to the cheapest available instance matching your requirements. On-demand and spot GPU rental options are surfaced from the entire provider network, giving teams multi-cloud flexibility without managing multiple accounts. The fastest way to find and launch the lowest-cost GPU for any AI training or inference workload.
- 30+ provider network
- Single API
- Automatic cheapest-price routing
- Wide GPU selection
Live GPU Pricing
Region Coverage
Popular Comparisons
CoreWeave — specialist provider
CoreWeave is a purpose-built GPU cloud offering H100 SXM5, H200, and A100 clusters with InfiniBand and NVLink interconnects for large-scale AI training and LLM fine-tuning. On-demand and reserved H100 instances are available across US East, US West, and EU regions, with some of the highest GPU density and lowest latency networking of any specialist cloud. A top choice for AI labs and enterprises running multi-node distributed training at scale.
Shadeform — marketplace provider
Shadeform is a GPU cloud aggregator that provisions H100, A100, RTX 4090, and many other GPU types across 30+ underlying cloud providers through a single unified API, automatically routing to the cheapest available instance matching your requirements. On-demand and spot GPU rental options are surfaced from the entire provider network, giving teams multi-cloud flexibility without managing multiple accounts. The fastest way to find and launch the lowest-cost GPU for any AI training or inference workload.
Billing model comparison
CoreWeave uses a On-demand, Reserved billing model with a minimum commitment of None. Shadeform uses On-demand, Spot billing with a None minimum. Both providers offer flexible billing options — compare the live pricing table above to find the best rate for your specific GPU model and workload duration.
Which workloads each provider suits best
CoreWeave is best suited for: Large-scale AI training, LLM fine-tuning, High-throughput inference. Its key strengths are highest gpu density, infiniband networking, kubernetes-native. Shadeform is best suited for: Teams wanting multi-cloud flexibility, Cost-optimized provisioning, Spot-tolerant workloads. Its key strengths are 30+ provider network, single api, automatic cheapest-price routing. Marketplace providers aggregate GPU supply from multiple sources, often offering the lowest spot rates but with more variable availability and less predictable performance compared to dedicated providers.
Support tiers and region coverage
CoreWeave offers Standard → Enterprise support across 3 regions (US-East, US-West, EU-West). Shadeform offers Community → Enterprise support across 4 regions (US, EU, APAC and 1 more). Shadeform's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: CoreWeave vs Shadeform
CoreWeave was founded in 2017 and is headquartered in Roseland, NJ. Shadeform was founded in 2023 and is headquartered in San Francisco, CA. CoreWeave has 6 years more operational history than Shadeform, which may matter for teams evaluating provider stability and long-term contract risk. Use the live pricing table above to compare current on-demand and spot rates for specific GPU models, and the region map to verify coverage in your target geography.