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Tinley Park · September 9, 2026
Nate Herk | AI AutomationSep 6, 2026

100 Hours Testing GPT-6 Astra vs Fable 5.1. What You Need to Know.

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What it covers

This video compares GPT-6 Astra and Claude Fable 5.1 across 15 practical use cases, including presentations, sales copy, browser tasks, video editing, and software building. The creator reviews both outputs for each test, shares which model they preferred, and compares the time and cost to guide their day-to-day AI workflow.

The outline

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  1. 0:00

    Intro

    The intro sets up the 100-hour comparison test between GPT-6 Astra and Claude Fable 5.1.

  2. 0:44

    Experiment 1

    Experiment 1 tests the models on a first use case and compares their outputs, preference, time, and cost.

  3. 4:11

    Experiment 2

    Experiment 2 tests the models on a second use case and compares their outputs, preference, time, and cost.

  4. 6:27

    Experiment 3

    Experiment 3 tests the models on a third use case and compares their outputs, preference, time, and cost.

  5. 8:42

    Experiment 4

    Experiment 4 tests the models on a fourth use case and compares their outputs, preference, time, and cost.

  6. 11:51

    Experiment 5

    Experiment 5 tests the models on a fifth use case and compares their outputs, preference, time, and cost.

  7. 14:22

    Experiment 6

    Experiment 6 tests the models on a sixth use case and compares their outputs, preference, time, and cost.

  8. 17:44

    Experiment 7

    Experiment 7 tests the models on a seventh use case and compares their outputs, preference, time, and cost.

  9. 20:12

    Experiment 8

    Experiment 8 tests the models on an eighth use case and compares their outputs, preference, time, and cost.

  10. 22:19

    Experiment 9

    Experiment 9 tests the models on a ninth use case and compares their outputs, preference, time, and cost.

  11. 25:31

    Experiment 10

    Experiment 10 tests the models on a tenth use case and compares their outputs, preference, time, and cost.

  12. 27:33

    Experiment 11

    Experiment 11 tests the models on an eleventh use case and compares their outputs, preference, time, and cost.

  13. 30:00

    Experiment 12

    Experiment 12 tests the models on a twelfth use case and compares their outputs, preference, time, and cost.

  14. 30:51

    Experiment 13

    Experiment 13 tests the models on a thirteenth use case and compares their outputs, preference, time, and cost.

  15. 32:28

    Experiment 14

    Experiment 14 tests the models on a fourteenth use case and compares their outputs, preference, time, and cost.

  16. 34:53

    Experiment 15

    Experiment 15 tests the models on a fifteenth use case and compares their outputs, preference, time, and cost.

  17. 36:37

    Conclusion

    The conclusion summarizes which model performed better overall and how the creator will choose between them for day-to-day work.

Workflow over benchmarks

Solo builders need practical comparisons of time and cost across real tasks like presentations and software building. Evaluating outputs for specific use cases helps guide day-to-day AI workflow decisions.