Frontier models are fungible: developer swaps mid-project across labs with similar results
jd_pressman · x · 2026-10-26
jdpressman argues that from a technological standpoint, half a dozen labs train base models on the same public internet corpus with broadly similar architectures and training objectives, then post-train with similar RL methods on similar task suites.
As a result, frontier models from DeepSeek, Meta, Google, Anthropic, GLM and others seem "fungible" to him: they produce similar results on complex software work, and he can even swap them mid-project. A practitioner's view reinforcing the frontier-model homogenization thesis.
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