GPT-6 Astra: per-task cost and five token-saving rules
Artificial Analysis index shows Astra at ~27K tokens and $1.35 per task, cheaper than Opus 5.5 and Fable 5.1 though scoring lower, with rules on input caps, caching and output limits.
Sam Altman's new model uses 4x fewer tokens than Claude Opus. and costs a third of Fable GPT-6 ASTRA: $1.35 A TASK. CLAUDE FABLE 5.1: $3.90. SAME BENCHMARK RUN you pay for every token a model writes to sound smart. Astra barely writes any Artificial Analysis ran the full index: GPT-6 Astra → ~27K tokens, $1.35 Opus 5 → ~73K, $1.83 Opus 5.5 → ~119K, $2.38 Fable 5.1 → ~78K, $3.90 honest part: Fable 5.1 still scores higher on that index. Astra wins on what you pay per answer and the cheap price only holds if you follow 5 rules. steal this: 1. stay under 272K input. cross it and the WHOLE request bills at 2x input and 1.5x output. 500K in + 32K out = $12.40 for one call 2. reuse your context. cached input is $1 per 1M instead of $10 3. cap output. Astra is short by default. type "explain in detail" and you're paying Claude prices on an OpenAI model 4. hand repeat work to a Dot. it runs Astra on its own cloud computer with 4,000+ apps and keeps going after you close ChatGPT 5. write Custom Rules first: allow, approve, prohibit. password changes always wait for you OpenAI's own numbers vs Fable 5.1: BenchCAD Vision2Code → 95.9 vs 84.3 Terminal-Bench Science → 64.6 vs 52.6 I moved my research runs to Astra and kept every prompt under 272K. full price grid is in the image, ready to copy save this before your first $30 call ↓
This post quotes another post: x.com/donatelloxpro/status/2109320196649619552