1021: We got addicted to an AI model we can't talk about

Where this was said

Local vs Cloud AI Model Hosting

At 31:35 · chapter starts 30:27

Wes asks the inevitable: are AI inference costs going to spiral into thousands per employee per month? Dax has actual data to offer. At their 5x surge level, OpenCode's inference spend amounts to roughly 15% of their payroll — notable, but manageable for a tech company. ^{[1] — Dax Raad "AI model cost ~15% of payroll: At 5x usage, OpenCode's AI inference costs represent roughly 15% of their total payroll — a manageable overh…" 28:44 Play} And the structural trajectory is downward. His estimate: Anthropic and OpenAI are currently running approximately 90% margin on inference, excluding R&D. Breakeven is 10x cheaper than current prices. ^{[2] — Dax Raad "Dax estimates Anthropic and OpenAI are running ~90% margins on inference, not counting R&D. That means breakeven is 10x cheaper than curren…" 29:10 Play} Training losses are separate — they don't factor into inference economics. For open-source models, OpenCode can already host at a 70% discount to cost even using GPU middlemen. Direct GPU ownership would approach those same 90% margins. The narrative that OpenAI and Anthropic are perpetually unprofitable confuses training investment with inference margins — these are very different line items on the P&L.

Technology

5x token usage increase

1021: We got addicted to an AI model we can't talk about · Jul 15, 2026

OpenCode's team increased monthly token usage by 5x after getting early access to an unreleased next-generation AI model.

30:47 – 31:20

♥ 0