@meta
  v: 1
  route: /gpu
  generated: 2026-06-10T07:18:04.635Z

@intent
  purpose:    Browse every GPU in the catalog. Find a card that fits a budget.
  audience:   ai-engineer, self-hoster, homelab-buyer
  capability: list_all_gpus, compare_by_vram, drill_into_card

@state
  total: 42
  families[8]{id,label,count}:
    rtx-50,RTX 50,4
    rtx-40,RTX 40,8
    rtx-30,RTX 30,6
    apple,Apple Silicon,9
    workstation,Workstation,4
    datacenter,Datacenter,5
    amd,AMD,3
    intel,Intel,3
  vram_min_gb: 8
  vram_max_gb: 512
  slugs[42]: rtx-3060, rtx-3070, rtx-3080, rtx-3080-ti, rtx-3090, rtx-3090-ti, rtx-4060, rtx-4060-ti, rtx-4070, rtx-4070-s, rtx-4070-ti-s, rtx-4080, rtx-4080-s, rtx-4090, rtx-5070, rtx-5070-ti, rtx-5080, rtx-5090, m2-max-64, m2-ultra-192, m3-max-64, m3-max-96, m4-pro-64, m4-max-128, m3-ultra-512, m5-pro-64, m5-max-128, a6000, rtx-6000-ada, rtx-6000-pro, l40s, h100, h200, b200, dgx-spark, h100-nvl-2x, rx-7900-xtx, w7900, mi300x, arc-b580, arc-pro-b60, gaudi-3

@actions
  - id: view_calculator
    method: GET
    href: /#calculator
  - id: view_math
    method: GET
    href: /the-math
  - id: browse_models
    method: GET
    href: /model/

@context
  > Index of all GPUs the calculator knows about. 40 cards grouped into 8 families (RTX 50/40/30, Apple, workstation, datacenter, AMD, Intel). Each card links to a detail page with bandwidth, FP16 compute, weights budget at ctx 8K, and the precomputed fit table against the 20-model catalog.

@nav
  self:      /gpu/
  parents:   [/]
  peers:     [/model/]
  drilldown: /gpu/rtx-4090