Easy access to GPU pricing data for major cloud providers: AWS, Azure, GCP, etc. The catalog includes details about prices, locations, CPUs, RAM, GPUs, and spots (interruptible instances).
Usage
import gpuhunt
items = gpuhunt.query(
min_memory=16,
min_cpu=8,
min_gpu_count=1,
max_price=1.0,
)
print(*items, sep="\n")
List of all available filters:
provider: name of the provider to filter by. If not specified, all providers will be used. One or manycpu_arch: CPU architecture, one of:x86,armmin_cpu: minimum number of CPUsmax_cpu: maximum number of CPUsmin_memory: minimum amount of RAM in GBmax_memory: maximum amount of RAM in GBmin_gpu_count: minimum number of GPUsmax_gpu_count: maximum number of GPUsgpu_vendor: GPU/accelerator vendor, one of:nvidia,amd,google,intelgpu_name: name of the GPU to filter by. If not specified, all GPUs will be used. One or manymin_gpu_memory: minimum amount of GPU VRAM in GB for each GPUmax_gpu_memory: maximum amount of GPU VRAM in GB for each GPUmin_total_gpu_memory: minimum amount of GPU VRAM in GB for all GPUs combinedmax_total_gpu_memory: maximum amount of GPU VRAM in GB for all GPUs combinedmin_disk_size: minimum disk size in GB (not fully supported)max_disk_size: maximum disk size in GB (not fully supported)min_price: minimum price per hour in USDmax_price: maximum price per hour in USDmin_compute_capability: minimum compute capability of the GPUmax_compute_capability: maximum compute capability of the GPUspot: ifFalse, only ondemand offers will be returned. IfTrue, only spot offers will be returned
Advanced usage
Every provider catalog is published and versioned independently, so a provider that fails
to be collected keeps its previous catalog while the other providers are updated. Passing
a version to load() requests that version from every provider:
from gpuhunt import Catalog
catalog = Catalog()
catalog.load(version="20260818-42")
items = catalog.query()
print(*items, sep="\n")
Supported providers
- AWS
- Azure
- CloudRift
- Verda
- GCP
- JarvisLabs
- LambdaLabs
- Nebius
- OCI
- Runpod
- Vast AI
- Vultr
See also
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- Uploaded via:
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