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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 many
  • min_cpu: minimum number of CPUs
  • max_cpu: maximum number of CPUs
  • min_memory: minimum amount of RAM in GB
  • max_memory: maximum amount of RAM in GB
  • min_gpu_count: minimum number of GPUs
  • max_gpu_count: maximum number of GPUs
  • gpu_name: name of the GPU to filter by. If not specified, all GPUs will be used. One or many
  • min_gpu_memory: minimum amount of GPU VRAM in GB for each GPU
  • max_gpu_memory: maximum amount of GPU VRAM in GB for each GPU
  • min_total_gpu_memory: minimum amount of GPU VRAM in GB for all GPUs combined
  • max_total_gpu_memory: maximum amount of GPU VRAM in GB for all GPUs combined
  • min_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 USD
  • max_price: maximum price per hour in USD
  • min_compute_capability: minimum compute capability of the GPU
  • max_compute_capability: maximum compute capability of the GPU
  • spot: if False, only ondemand offers will be returned. If True, only spot offers will be returned

Advanced usage

from gpuhunt import Catalog

catalog = Catalog()
catalog.load(version="20240508")
items = catalog.query()

print(*items, sep="\n")

Supported providers

  • AWS
  • Azure
  • Cudo Compute
  • DataCrunch
  • GCP
  • LambdaLabs
  • OCI
  • RunPod
  • TensorDock
  • Vast AI

See also