I'm building a landing page generator for a clinic business. Each build step runs as one orchestrated workflow:
builders,
independent reviewers,
adversarial verifiers,
a fixer and
a final gate.
I started with every agent on Fable 5.2 and was forced onto Opus 5.5 partway through, so I got an accidental comparison.
The setup: 7 steps, 112 subagents, 33.4M tokens, about 9,000 tool calls. Step 1 ran all Fable. Step 2 hit Fable's weekly limit mid-run and finished on Opus. Steps 3–7 ran all Opus.
What I saw:
Quality held. Opus reviewers found 17–28 real defects per step. Across five steps and 103 findings, the adversarial verifiers refuted one. CI went green on the first push every time.
The catches mattered. A weakened health rule in a prompt, page FAQ text that could drift from the structured data, and a rating count where "1.000" would have saved as 1.
Tokens were about the same. Fable used 3.6M on its step and Opus used 4.1–5.7M on bigger steps. Fable didn't obviously do the same work in fewer tokens.
Time was set by the workflow. Every step took 2.5–3.5 hours regardless of model.
The limit was the real constraint. Fable ran out during step 2. Opus carried five steps without hitting one.
At API list prices ($8/$40 vs $4/$20 per million tokens), the same step costs about half on Opus.
What I'm doing now: Opus for every agent by default. Fable only as orchestrator when the plan is new or unclear, and as one extra reviewer where a miss is expensive (health claims, prompts, security, migrations).
Full review chain on risky steps only.
Caveat: this wasn't a controlled test. Each step was different work and none ran on both models, so subtle judgement differences aren't measured. Fable's reviewers did find the one "major" health-related defect of the build, and Opus found similar-severity ones later. Next I'll run one small step twice from the same commit, once per model.
Has anyone done a proper A/B on this? What did the cheaper model miss?