Python 3.12 vs 3.13 JIT: 16% Faster or 2x Slower?

The JIT Everyone Hyped Didn't Help My Code

Python 3.13 shipped with experimental JIT compilation, and the headlines promised 2-5x speedups. I ran my typical data processing scripts—Pandas wrangling, numerical loops, some regex—and saw... 16% slower performance on half the benchmarks.

Turns out the JIT helps a very specific workload profile, and if you don't fit it, the overhead actually costs you. The bytecode changes between 3.12 and 3.13 also matter more than most people realize. Let me show you what actually got faster, what got slower, and why.

What Changed Under the Hood

Python 3.13 introduced two major performance features:

1. Experimental JIT compiler (disabled by default, enable via PYTHON_JIT=1)
2. New bytecode instruction set with specialized opcodes for common patterns

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