π I Built an AI Code Conversion Benchmark Platform
Over the last few weeks Iβve been working on a project called CodexConvert. It started as a simple idea: What if we could convert entire codebases using multiple AI models β and automatically bench...
Source: DEV Community
Over the last few weeks Iβve been working on a project called CodexConvert. It started as a simple idea: What if we could convert entire codebases using multiple AI models β and automatically benchmark which one performs best? So I built a tool that does exactly that. π Multi-Model Code Conversion CodexConvert lets you run the same conversion task across multiple AI models at once. For example: Python β Rust JavaScript β Go Java β TypeScript You can compare outputs side-by-side and immediately see how different models perform. π Automatic Benchmarking Each model output is evaluated automatically using three metrics: β Syntax Validity β Structural Fidelity β Token Efficiency Scores are normalized to a 0β10 scale, making it easy to compare models. π Built-in Leaderboard CodexConvert keeps a local benchmark dataset and generates rankings like: Rank Model Avg Score π₯ GPT-4o 9.1 π₯ DeepSeek 8.8 π₯ Mistral 8.4 You can also see which models perform best for specific language migrations. οΏ½
