Local AI vs cloud API pricing frontier

This chart contrasts hardware you can own with the most expensive frontier cloud API output prices. The point isn't that every local machine beats every cloud bill - it's that the ceiling for cloud API pricing is rising fast, while a one-time hardware purchase runs open models forever at zero marginal cost.

Local hardware frontier

NVIDIA DGX Station 748GB
748GB unified - Server
Mac Studio M4 Ultra 512GB
512GB unified - Desktop
Mac Studio M5 Ultra 512GB
512GB unified - Desktop
Mac Studio M3 Ultra 512GB
512GB unified - Desktop
Mac Studio M3 Ultra 256GB
256GB unified - Desktop
Mac Studio M5 Ultra 256GB
256GB unified - Desktop
Mac Studio M4 Ultra 192GB
192GB unified - Desktop
GMKtec EVO-X5 Pro 192GB
192GB unified - Desktop
MacBook Pro 16-inch M5 Max 128GB
128GB unified - Laptop
TT-QuietBox 2
128GB VRAM - Desktop
GMKtec EVO-X2 128GB
128GB unified - Desktop
MacBook Pro 16-inch M4 Max 128GB
128GB unified - Laptop
Framework Desktop 128GB
128GB unified - Desktop
AMD Ryzen AI Halo 128GB
128GB unified - Desktop
NVIDIA DGX Spark 128GB
128GB unified - Server
Mac Studio M4 Max 96GB
96GB unified - Desktop
NVIDIA RTX PRO 6000 Blackwell 96GB
96GB VRAM - Gpu-card
Mac Studio M3 Ultra 96GB
96GB unified - Desktop
NVIDIA RTX PRO 6000 Blackwell Max-Q 96GB
96GB VRAM - Gpu-card
Mac Studio M5 Ultra 96GB
96GB unified - Desktop

Browse more hardware and see which models each config runs: All hardware configs.

Cloud API frontier (output price)

GPT-5.5
OpenAI
$30
per 1M tokens
Claude Opus 4.8
Anthropic
$25
per 1M tokens
GPT-5.4
OpenAI
$15
per 1M tokens
Claude Sonnet 5
Anthropic
$10
per 1M tokens
Claude Haiku 4.5
Anthropic
$5
per 1M tokens
GPT-5.4 mini
OpenAI
$4.5
per 1M tokens
GPT-5.4 nano
OpenAI
$1.25
per 1M tokens

Prices are pulled from the catalog as reported by providers. See per-model provider tables: Pricing index.

What this means in practice

No per-token bill. After the hardware is paid for, inference is free. Cloud output prices compound with every API call.
No rate limit. A local machine is bottlenecked only by its own memory and compute, not a provider's queue.
No switch-off. Open-weight weights live on your drive. No API deprecation or policy change can remove them.