Pat Simmons compares GPT-5.6 Sol with Fable 5, Opus 4.8 and GPT-5.5 across ten practical tests. He first distinguishes the Sol, Terra and Luna tiers, then explains that Sol targets demanding agent work while higher effort modes can coordinate multiple agents. His testing covers interactive 3D builds, a first-person game, data-driven maps and a cinema knowledge graph.
The coding results are mixed. GPT-5.6 Sol produces strong work on the Milky Way map, the cinema knowledge graph and several repaired builds, but initially fails the Rubik's Cube test and misses key details in a 3D apartment. Pat Simmons concludes that Fable remains the stronger coding orchestrator, while Sol is competitive on narrower implementation tasks.
GPT-5.6 Sol performs more consistently on knowledge work. It leads Pat Simmons's tests for an interactive graphic novel, a text adventure, a launch presentation and an airline rebrand. He recommends choosing models by task: use a stronger orchestrator for architecture, route knowledge-heavy work to Sol and assign lower-cost models to simpler jobs.
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