🚀 I Built an AI Code Conversion Benchmark Platform

Over the last few weeks I’ve been working on a project called CodexConvert. It started as a simple idea: What if we could convert entire codebases using multiple AI models — and automatically benchmark which one performs best? So I built a tool that does exactly that. 🔁 Multi-Model Code Conversion CodexConvert lets you run the same conversion task across multiple AI models at once. For example: Python → Rust JavaScript → Go Java → TypeScript You can compare outputs side-by-side and immediately see how different models perform. 📊 Automatic Benchmarking Each model output is evaluated automatically using three metrics: ✔ Syntax Validity ✔ Structural Fidelity ✔ Token Efficiency Scores are normalized to a 0–10 scale, making it easy to compare models. 🏆 Built-in Leaderboard CodexConvert keeps a local benchmark dataset and generates rankings like: Rank Model Avg Score 🥇 GPT-4o 9.1 🥈 DeepSeek 8.8 🥉 Mistral 8.4 You can also see which models perform best for specific language migrations. �