Cloud GPU & Accelerator Pricing
Live blended pricing across spot, on-demand, and reserved instances for 37 GPU and AI accelerator types. Updated daily from major cloud providers.
High-performance accelerators optimised for AI model training, fine-tuning, and HPC workloads
Cost-efficient accelerators optimised for deploying and serving AI models in production
FPGAs, specialised chips, and accelerators for custom workloads
GPU Comparisons
Side-by-side comparisons of 25 GPU and AI accelerator pairs — H100 vs A100, H100 vs MI300X, T4 vs L4, and more.
Understanding Cloud GPU Pricing
Cloud GPU pricing varies significantly based on the accelerator type, cloud region, and pricing model. Signwl tracks pricing across three tiers — spot (preemptible), on-demand, and reserved (committed use) — and presents a blended average that reflects the true cost landscape for each accelerator.
Training-class GPUs like the NVIDIA H100, H200, and AMD MI300X command premium pricing due to their high compute throughput and memory bandwidth, which are essential for training large AI models. Inference-class GPUs like the L4, T4, and L40S offer lower price points optimised for serving models in production, where cost-per-query matters more than raw TFLOPS.
Regional pricing differences can be substantial — the same GPU may cost 30–50% more in certain regions due to supply constraints, power costs, and local demand. Signwl aggregates pricing data from major cloud providers across all available regions to give a complete picture of the global GPU cost landscape.
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