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GPT-5.6 Sol vs. Claude Fable: Why OpenAI’s new model crushes my benchmark

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 ↗

At a glance

WHAT IT’S REALLY ABOUT

GPT-5.6 Sol beats Claude Fable on Claire’s real-world benchmark

  1. 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.
  2. Claire’s “How I AI” benchmark blends an LLM judge (GPT-5.5) with her own taste test (70% Claire / 30% machine), and under that weighting GPT-5.6 Sol wins overall by a meaningful margin.
  3. Sol is praised for producing more functional, opinionated, and less “template-slop” prototypes than Fable, especially on dense/technical UIs like ops dashboards and incident triage tools.
  4. Fable is credited as highly intelligent and capable for complex technical work, but Claire finds it overly pedantic and hard to collaborate with due to unnatural, overly-engineered communication.
  5. Beyond the benchmark, Claire highlights Sol’s practical effectiveness in breaking through overly rigid architectures, plus strong workflows for video clipping/editing and high-throughput browser automation via Codex + @Chrome.

IDEAS WORTH REMEMBERING

5 ideas

Sol wins because it’s practically shippable, not just theoretically smart.

Claire’s core critique is that Fable can be “hyper-intelligent” yet overly constrained and pedantic, while Sol more readily loosens constraints to deliver usable product outputs aligned with end-user goals.

Pricing favors Sol, making it easier to standardize on for frequent work.

She cites Sol at ~$5/M input and ~$30/M output tokens versus Fable at ~$10/M input and ~$50/M output, arguing the cost gap matters when prototyping and iterating heavily.

Functionality inside prototypes is a primary differentiator in real workflows.

In side-by-sides (ops dashboard, creative pack site, incident triage, habit trackers), Sol more often produced interfaces where expected interactions actually worked and the layout supported real task flow.

Terra can be the better pick for straightforward business writing and PRDs.

Despite Sol’s overall win, Claire preferred Terra’s PRD outputs as “streamlined and to the point,” implying Terra may be optimal when clarity and brevity beat flourish.

Sonnet remains Claire’s favorite for “agentic voice,” even if it’s imperfect.

For assistant-like interactions (rescheduling meetings, handling deploy stress), she rates Sonnet as most human-sounding, while Sol (and especially Fable) is criticized for cringe phrasing and em-dash-heavy delivery.

WORDS WORTH SAVING

5 quotes

I did blind taste test these, and so I do really feel like it did a good job.

Claire Vo

I hate slop. I hate slop. I hate slop. We all hate slop. It's the worst. It's the worst part of AI.

Claire Vo

I hate talking to Fable 5 because it talks to me like an engineer that has never met a human before. It's like its first day on Earth.

Claire Vo

If you would take away, like, one highlight, um, difference between Fable and Sol is, like, Fable is theoretically hyper-intelligent and Sol is practically effective.

Claire Vo

The problem is when you're building products, exact precision is neither helpful nor possible.

Claire Vo

GPT-5.6 Sol/Terra/Luna positioningAPI pricing comparison: Sol vs. FableHow I AI benchmark design and scoring (70/30 weighting)Prototype quality: functionality, hierarchy, originalityPRD writing style: crisp vs. “AI writing” slopAgentic voice and collaboration (em-dash “slop talk”)Codex workflows: prototyping, video editing, browser use (@Chrome)

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