Coding Scaling Laws Vary by Language; Python's Dynamic Typing Causes Negative Transfer
mdancho84 · x · 2026-08-12
The author shares insights on how models learn programming languages:
- Coding scaling laws aren't uniform: Different languages need varying amounts of data. Python and JS, despite being the most used, can be trickier for models to master than some enterprise languages.
- Python is weirdly hard for models: Mixing languages in pretraining helps until dynamic typing creates negative transfer compared to statically typed languages. Conversely, pairs like Java↔Cor JS↔TS show strong synergy.
Related event: Divergent Coding Scaling Laws and RLVR Empowering Small Models(2 posts)→
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