Codeflash blog

How a 13.7× Speedup Landed in vLLM - and What It Teaches Us About Writing Fast Python

How Codeflash sped up vLLM token decoding by 13.7x

Eliminating Object Allocation Overhead: A 41.83x Python Performance Win Through Path Manipulation Optimization

Why Python’s deepcopy Can Be So Slow (and How to Avoid It)

The comprehensive copying by deepcopy is convenient but expensive. In this post we discuss why is deepcopy is expensive, and show how avoiding the slowdown associated with deepcopy can lead to upto 180x speedups.

Codeflash Named a Gartner Cool Vendor in Software Quality & Testing

Codeflash has been named a 2025 Gartner® Cool Vendor in the “Software Quality and Testing” category!

The AlphaEvolve Moment: Why AI-Powered Code Optimization Is Now Essential

While AlphaEvolve represents a significant research milestone, Codeflash offers a practical, accessible solution for developers today. Our AI-powered tool optimizes Python codebases, ensuring high performance and efficiency.

How Roboflow Accelerated Computer Vision Model Performance by 25% with Codeflash

LLMs struggle to write performant code

If you use AI coding assistants, you are unfortunately shipping a lot of slow, un-optimized code. In this blog, I will show why AI struggles with writing performant code, and show how you can always ship performant code even when using AI coding assistants.

What is Continuous Optimization?

Continuous Optimization means that all new code being written is continuously optimized for performance, before it is deployed - ensuring it runs at peak performance in production. This blog shows how can we all ship features quickly while ensuring they run fast.

How Codeflash sped up Pydantic code by 34% - Recursion to Stack Optimization

With many complex functions, the most natural way to write them is with a recursive implementation. However, a recursive implementation can be slow in Python because recursive calls can be expensive. Is there a better way? Yes! We can remove the recursion and manage an explicit