Published: 2026-09-06

GPT-6 Astra vs Fable 5.1 across 15 use cases, with cost and time for each

Chapters / key moments (click to jump — plays here on the page)

The two models launched two days apart at the same $10/$50 headline price, so the interesting question is not which is smarter — it is which is better per task, and this test records time and cost on every one. The behavioural difference that shows up repeatedly matters more than any single result: Astra asks clarifying questions before it starts; Fable takes the prompt and runs. On a consulting deck that made Fable faster to a usable artifact. On tax work, where the questions surfaced real assumptions, it made Astra the one to trust. Neither is universally right, and knowing which behaviour you want is now part of picking a model.

Source video

"I Tested GPT-6 Astra vs Fable 5.1 on 15 Real Use Cases" by Nate Herk — Watch on YouTube →

Recorded results, first four use cases

Use case	Better output	Fable 5.1 time / cost	Astra time / cost
McKinsey-style consulting deck (branded, sourced)	Fable 5.1 — consistent footer, columns, structure; more professional, though wordy for presenting	37 min / $26	23 min / $12
Sales landing page copy (~2,800 vs ~1,300 words)	Fable 5.1 — answered objections directly ("will this get me hired", tuition, who it is not for)	4 min / ~$4	3 min / $1.43
Personal tax analysis, two quarters	Astra — asked seven clarifying questions first, more tailored, full 3,739-row transaction ledger	22 min	40 min
Overall behavioural pattern	—	Takes the prompt and runs	Asks clarifying questions before starting

Costs and times as recorded in the video on the reviewer's own subscriptions; both models were run at high effort through their respective desktop apps. Treat them as one practitioner's measurements, not benchmarks.

Gotchas & Caveats

These are one practitioner's runs on his own subscriptions, not a benchmark. Single-shot prompts, no iteration, both models on high effort. Different effort levels would move both the cost and the quality — see our write-up of Anthropic's own effort-level guidance.
Several judgements are explicitly subjective — the reviewer says he is not a copywriter and would defer to someone on his team for the sales-letter verdict.
The tax use case is largely blurred in the video for privacy, so the comparison there rests on his description of the deliverables rather than on visible output.
Costs reflect subscription usage rather than API list prices. Check current rates in our cost calculator, which carries both models as of this week.

Key Takeaways

Astra asks, Fable runs. This showed up across use cases and is the most portable finding — on the tax task Astra asked seven questions before starting, which the reviewer says is precisely why he trusted its output more there.
On the consulting deck, Fable produced the better artifact but Astra was 14 minutes faster and roughly half the cost. The reviewer poses the right follow-up: if you spent Astra's cost advantage on a second improvement pass, would you end up ahead? That is the real comparison once headline prices match.
Cost per task diverged sharply from cost per token. On the sales letter Fable came in around $4 against Astra's $1.43; on the deck Fable was $26 against $12. Same listed rates, very different bills — because the models spend different numbers of tokens reaching an answer.
For long-form copy, Fable's extra length was the reason it won, not a flaw — it covered objections a shorter draft skipped. Length is not automatically padding on this kind of task.
On structured financial work, tailoring beat speed. Astra returned a fuller, more readable deliverable including the complete transaction ledger, and took longer to do it.
The reviewer notes his team has recently preferred GPT models for writing, reversing the older assumption that Claude dominated prose — worth re-testing your own defaults rather than inheriting them.

What you can actually set up from this

Extracted from the video's own transcript — the specifics the original summary left out.

Reproducible steps

How he ran it
He gave GPT-6 Astra (in Codex) and Claude Fable 5.1 the same prompts across 15 of his own work use cases, and logged the winner, wall-clock time and cost for each; timestamps are in the video description.
What he reported for the first nine
Consulting-style deck: Fable won (37 minutes and about $26, versus Astra's 23 minutes and $12). Sales letter: Fable won. Tax analysis: Astra won, but took 40 minutes and about $22 versus 22 minutes and $13. Subscription audit across two email accounts: Astra won, about $12.50 versus about $50 (Fable left one sheet empty). Meeting analysis: Astra won, $5.12 versus $46. 60-second event recap reel: Astra by a slight edge, 30 minutes and $16 versus 50 minutes and $26. Sizzle reel: Astra won. Browser game: Astra won on feel. The evaluation SaaS build is compared next in the video.
Watch for the clarifying-questions difference
He noticed Astra asked more questions up front (seven on the tax task) while Fable took the prompt and ran; he says that alone made him more confident in Astra's tax output.

Gotchas

He says the models are now so strong that the question is presentation: for the deck, he found Fable's output tidier but too wordy to present, and Astra's less structured.
He stresses these are subjective calls on his own tasks and recommends running your own use cases.
He reports his own Fable cost anomaly: $46 for the meeting analysis even though active agent time was about six minutes, and he could not explain where the tokens went.
He says he has used three Codex subscriptions, four Claude subscriptions and thousands of dollars of usage credits making the video.