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GPT-5.6 Sol: Better AND cheaper than Fable

GPT-5.6 Sol is back, and I ran it through my full How I AI vibe benchmark against GPT-5.6 Terra, Luna, Claude Fable 5, and Sonnet 5 across five categories: PRDs, prototypes, wireframes, debugging, and agentic voice. Sol won by a meaningful margin on my Claire Weighted Index (70% my taste, 30% Terminal Bench 2.1), and I also tested two use cases I can't stop thinking about: building a gamified homework tracking app for my kids in one shot with Codex, and browser automation with Chrome that burned through 500 LinkedIn replies while I did literally nothing. *What you’ll learn:* 1. How I scored five AI models (including GPT 5.6 Sol, Fable 5, and Sonnet 5) using my “Claire Weighted Index” benchmark across PRDs, prototypes, code, and agentic voice 2. The difference between GPT-5.6 Sol (Terra) and Sol for PRD writing 3. How Fable’s precision and pedantry made it harder to collaborate with, and the exact moment Sol broke through where Fable got stuck 4. Why Sonnet 5 is still my go-to for agentic voice in OpenClaw, even after this whole benchmark 5. How I used GPT-5.6 Sol in Codex to build a fully gamified homework tracking app for my kids in one shot 6. The video editing use case that saved me hours clipping a talk I gave at Cursor’s event 7. How to use Codex plus GPT-5.6 and Chrome for browser automation, and why this is my single most-loved use case right now *In this episode, I cover:* (00:00) Intro (01:10) The three GPT-5.6 models: Sol, Terra, Luna (02:17) Pricing: Sol vs. Fable API costs (03:24) The How I AI benchmark (05:03) Claire-weighted Index results (07:00) Per-task winners: prototypes, PRDs, agentic voice (11:59) What Claire actually rewards (13:20) Full-fidelity prototype side-by-sides (Sol vs. Fable) (17:45) Wireframes (18:19) Agentic voice (19:15) Where Sol is better than other models (23:56) Gamified kids’ homework app, built in one shot (28:02) Fable’s pedantry problem and how Sol broke through it (31:49) Two bonus use cases: video editing and browser use (35:08) Final summary and model recommendations *Tools referenced:* • GPT 5.6 (Sol, Terra, Luna): https://help.openai.com/en/articles/20001325-a-preview-of-gpt-56-sol-terra-and-luna • Codex: https://openai.com/codex • ChatPRD: https://www.chatprd.ai/ • CapCut: https://www.capcut.com/ • Math Academy: https://www.mathacademy.com/ *Other references:* • Cursor event where Claire spoke on the future of PM: https://www.youtube.com/watch?v=4CAFK-rc26A • ChatPRD blog (where benchmark outputs will be published): https://www.chatprd.ai/ *Where to find Claire Vo:* ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo _Production and marketing by https://penname.co/._ _For inquiries about sponsoring the podcast, email jordan@penname.co._

Claire Vohost
Jul 9, 202636mWatch on YouTube ↗

Episode Details

EPISODE INFO

Released
July 9, 2026
Duration
36m
Channel
How I AI
Watch on YouTube
▶ Open ↗

EPISODE DESCRIPTION

GPT-5.6 Sol is back, and I ran it through my full How I AI vibe benchmark against GPT-5.6 Terra, Luna, Claude Fable 5, and Sonnet 5 across five categories: PRDs, prototypes, wireframes, debugging, and agentic voice. Sol won by a meaningful margin on my Claire Weighted Index (70% my taste, 30% Terminal Bench 2.1), and I also tested two use cases I can't stop thinking about: building a gamified homework tracking app for my kids in one shot with Codex, and browser automation with Chrome that burned through 500 LinkedIn replies while I did literally nothing. *What you’ll learn:*

  1. How I scored five AI models (including GPT 5.6 Sol, Fable 5, and Sonnet 5) using my “Claire Weighted Index” benchmark across PRDs, prototypes, code, and agentic voice
  2. The difference between GPT-5.6 Sol (Terra) and Sol for PRD writing
  3. How Fable’s precision and pedantry made it harder to collaborate with, and the exact moment Sol broke through where Fable got stuck
  4. Why Sonnet 5 is still my go-to for agentic voice in OpenClaw, even after this whole benchmark
  5. How I used GPT-5.6 Sol in Codex to build a fully gamified homework tracking app for my kids in one shot
  6. The video editing use case that saved me hours clipping a talk I gave at Cursor’s event
  7. How to use Codex plus GPT-5.6 and Chrome for browser automation, and why this is my single most-loved use case right now

*In this episode, I cover:* (00:00) Intro (01:10) The three GPT-5.6 models: Sol, Terra, Luna (02:17) Pricing: Sol vs. Fable API costs (03:24) The How I AI benchmark (05:03) Claire-weighted Index results (07:00) Per-task winners: prototypes, PRDs, agentic voice (11:59) What Claire actually rewards (13:20) Full-fidelity prototype side-by-sides (Sol vs. Fable) (17:45) Wireframes (18:19) Agentic voice (19:15) Where Sol is better than other models (23:56) Gamified kids’ homework app, built in one shot (28:02) Fable’s pedantry problem and how Sol broke through it (31:49) Two bonus use cases: video editing and browser use (35:08) Final summary and model recommendations *Tools referenced:*

*Other references:*

*Where to find Claire Vo:* ChatPRD: https://www.chatprd.ai/ Website: https://clairevo.com/ LinkedIn: https://www.linkedin.com/in/clairevo/ X: https://x.com/clairevo _Production and marketing by https://penname.co/._ _For inquiries about sponsoring the podcast, email jordan@penname.co._

SPEAKERS

  • Claire Vo

    host

    Host of “How I AI,” covering AI tools, model comparisons, and practical workflows.

EPISODE SUMMARY

In this episode of How I AI, featuring Claire Vo, GPT-5.6 Sol: Better AND cheaper than Fable explores gPT-5.6 Sol beats Claude Fable on Claire’s real-world benchmark OpenAI’s GPT-5.6 family is framed as three tiers—Sol (frontier), Terra (balanced), and Luna (cheap/high-volume)—with Sol positioned as Claire’s preferred daily driver.

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