--- title: The Optimization Ladder | daily.dev description: A comprehensive benchmarking study of every major Python optimization technique, from CPython version upgrades to Rust via PyO3. Using two Benchmarks Game... canonical: https://daily.dev/posts/the-optimization-ladder-jor2sohos twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: The Optimization Ladder | daily.dev og:description: A comprehensive benchmarking study of every major Python optimization technique, from CPython version upgrades to Rust via PyO3. Using two Benchmarks Game... og:url: https://daily.dev/posts/the-optimization-ladder-jor2sohos og:image: https://api.daily.dev/og/posts/jOR2soHOs.png og:image:alt: The Optimization Ladder og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # The Optimization Ladder **[Hacker News](https://daily.dev/sources/hn)** · 20 min read · 0 upvotes · 0 comments ## Summary A comprehensive benchmarking study of every major Python optimization technique, from CPython version upgrades to Rust via PyO3. Using two Benchmarks Game problems (n-body and spectral-norm) plus a real-world JSON pipeline, the author measures speedups at each 'rung': upgrading CPython (1.4x free), PyPy/GraalPy (6-66x), Mypyc (2.4-14x), NumPy (520x), JAX JIT (1,633x), Numba (56-135x), Cython (99-124x), and Rust (113-154x). Key findings: JAX achieves the fastest result overall (1,633x on spectral-norm), Cython and Rust are essentially tied on pure compute, and the real bottleneck in dict-heavy pipelines is json.loads() rather than the processing logic. The post includes detailed cost-benefit analysis for each approach and practical guidance on when to stop climbing. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Python Numbers Every Programmer Should Know](https://daily.dev/posts/python-numbers-every-programmer-should-know-dbwyosyik) · Planet Python · 4 upvotes · 0 comments - [CPython vs. PyPy: Which Python runtime has the better JIT?](https://daily.dev/posts/cpython-vs-pypy-which-python-runtime-has-the-better-jit--sxyfgcyzu) · InfoWorld · 0 upvotes · 0 comments - [benchmarking permutations](https://daily.dev/posts/benchmarking-permutations-s1ti8dbie) · Vincent D. Warmerdam · 1 upvotes · 0 comments - [Python picks up speed with a new JIT](https://daily.dev/posts/python-picks-up-speed-with-a-new-jit-0tjkgluas) · InfoWorld · 0 upvotes · 0 comments --- Tags: [#python](https://daily.dev/tags/python), [#performance](https://daily.dev/tags/performance), [#rust](https://daily.dev/tags/rust), [#numpy](https://daily.dev/tags/numpy) [View this post on daily.dev](https://daily.dev/posts/the-optimization-ladder-jor2sohos) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"The Optimization Ladder","url":"https://daily.dev/posts/the-optimization-ladder-jor2sohos","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/the-optimization-ladder-jor2sohos"},"datePublished":"2026-03-14T15:35:27.704Z","dateModified":"2026-03-14T15:35:52.856Z","description":"A comprehensive benchmarking study of every major Python optimization technique, from CPython version upgrades to Rust via PyO3. 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