GPT-5.6 vs. Claude Fable 5 for Physical AI, which performs best?

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We tested the latest frontier models in the Dyad agent on five modeling and simulation problems, comparing accuracy, cost, time, and work style.

Opening excerpt

We tested the latest frontier models gpt-5.6-terra in our agent, on five modeling and simulation problems of varying difficulty. Here are the results: claude-fable-5 0.889 weighted score $9.60 / trial · 16.1 min gpt-5.6-sol 0.814 weighted score $1.74 / trial · 13.4 min gpt-5.6-terra 0.786 weighted score $1.25 / trial · 12.6 min gpt-5.6-luna 0.727 weighted score $3.26 / trial · 25.0 min Physical AI lives or dies on whether the modeled physics is correct. A model of an aircraft, a separation column or a charged particle can compile and run cleanly while the physics it encodes is impossible. Agentic AI makes this failure mode worse, because agents steer by feedback from tests, and the tests are often written by the same agent. In domains like web development or compilers that loop works well enough, since correct behavior is contained and checkable.

There is also a trust problem with the numbers that already exist. Nobody takes the model providers’ self-reported benchmarks at face value, and for good reason: the provider publishing the score is the same party with every incentive to …

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