Frontier models still fail basic PDE solvers, benchmark post says
GaryMarcus · x · 2026-08-04
A retweeted benchmarking post claims frontier models repeatedly fail on basic nonlinear PDE solvers, while a neurosymbolic model is far more reliable and cheaper.
- The author says models such as GPT-5.6 Sol, Fable 5, and Kimi K3 still make serious mistakes in numerical stability, order of accuracy, and physical consistency.
- Even when they do succeed, the post claims stronger models can burn 100x+ more tokens than a lightweight neurosymbolic alternative.
- The argument is that a neurosymbolic architecture like Lanyon is needed for end-to-end correctness guarantees on scientific code.
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