CoreWeave — Inference & Compute Platform
Inference & ComputeLayer 1Usage-basedWhat is CoreWeave?
CoreWeave is a specialized cloud infrastructure provider founded in 2017 in New Jersey by Michael Intrator, Brian Venturo, Brannin McBee, and Peter Salanki. Originally started by three commodities traders, CoreWeave has grown into a leading GPU cloud platform built specifically for AI and machine learning workloads. Based in Livingston, New Jersey, with approximately 1,871 employees as of January 2026, CoreWeave offers on-demand access to NVIDIA H100 and A100 GPUs with significantly lower pricing than traditional hyperscalers. The platform provides Kubernetes-native orchestration, fast networking, and flexible scaling, making it popular with AI labs, research institutions, and startups that need large GPU clusters without long-term commitments. CoreWeave's infrastructure is designed from the ground up for GPU-accelerated workloads, offering up to 60% discounts over on-demand prices for committed usage, with transparent pricing that doesn't charge for data egress, IOPS, or core networking services.
Key Features
- ✓Large-scale GPU clusters (H100, A100)
- ✓InfiniBand networking for distributed training
- ✓Kubernetes-native orchestration
- ✓On-demand and reserved capacity
- ✓Bare-metal performance
Pros & Cons
Pros
- +Significantly lower GPU pricing compared to AWS, Azure, and GCP hyperscalers
- +Purpose-built for AI workloads with optimized networking and Kubernetes orchestration
- +Transparent pricing with no hidden fees for data egress or core services
- +Up to 60% discounts available for committed usage, excellent for predictable workloads
Cons
- -No free tier or trial period, requiring upfront payment commitment
- -Smaller ecosystem compared to major cloud providers may limit integration options
- -Less mature than hyperscalers in terms of managed services and tooling
- -À la carte pricing model requires careful calculation of total costs including CPU and RAM
CoreWeave Pricing
- ✓Pay-as-you-go pricing
- ✓Immediate availability
- ✓No commitments
- ✓Free data egress
- ✓Free VPC setup
- ✓Up to 60% discount
- ✓Reserved capacity
- ✓Predictable pricing
- ✓Priority support
- ✓Custom terms
Common Use Cases
AI companies and startups that need large-scale GPU clusters for training and inference
- •Large language model training
- •Distributed training across GPU clusters
- •High-performance inference at scale
- •AI startup compute infrastructure
- •Batch processing and fine-tuning
Using CoreWeave with Respan
CoreWeave and Respan together provide powerful GPU infrastructure with comprehensive AI observability. Run your models on CoreWeave's cost-effective GPUs while monitoring performance and costs with Respan.
- ✓Track costs across CoreWeave GPU instances to optimize your compute spending
- ✓Monitor model inference performance on CoreWeave infrastructure with Respan's detailed metrics
- ✓Compare GPU utilization and LLM costs across CoreWeave and other cloud providers
- ✓Debug model performance issues by correlating Respan traces with CoreWeave resource metrics
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Last verified: March 9, 2026