Running Fable subagents from a Fable orchestrator is a fast path to burning 30% of your weekly limit on nothing useful. The right pattern is Fable commanding cheaper models — Sonnet 5, GLM-5.2, or similar — for implementation work while Fable handles planning, context, and review.
Where this was said
At 57:56 · chapter starts 54:50
The pricing story around Fable is revealing. It launched at roughly $125 per million output tokens, then dropped to $50 — still 30–40% more expensive than Opus on a per-token basis, but Fable uses significantly fewer tokens per equivalent task. That means Fable often ends up cheaper than Opus in practice, which Theo argues is the death knell for Opus as a standalone model. [1] — Theo "Fable dropped from $125 to $50 per million output tokens, making it 30–40% pricier than Opus per token — but far cheaper overall because it…" 54:50 He's already made peace with paying API prices once the subscription window closes: he spent $150–$200 closing over 30 PRs in a single 5-hour session, and frames it as a magic button he'd press twice a day if he could. Ben agrees that any serious company would make the same calculation. The conversation turns to whether Opus 5 can survive in a world where Fable is this affordable — both hosts think Opus 5 needs to be priced lower than current Opus just to remain relevant.
Fable dropped from $125 to $50 per million output tokens, making it 30–40% pricier than Opus per token — but far cheaper overall because it uses fewer tokens. The result: Opus is dead. Theo won't maintain a $200/month sub for Opus alone, and thinks Opus 5 needs to be cheaper or it won't survive either.
Ben speculated that Fable (Mythos) is likely a 5 to 10 trillion parameter model, making it the largest publicly accessible frontier model by a wide margin.
Fable (Mythos) dropped from its originally announced ~$125 per million output tokens to ~$50, making it 30–40% more expensive than Opus but often cheaper due to lower token usage.
Ben accidentally ran Fable subagents on xHigh reasoning, burning through roughly 30% of a weekly usage allocation with negligible useful output.
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