CodeBurn
See where your AI coding spend actually goes
What it does
CodeBurn is a free, open-source tracker for AI coding costs. It reads the session files your tools already write - Claude Code, Cursor, Codex, Copilot, 40 in all, and shows every token and dollar by the task, model, project, and pull request that used it. The Optimize tab finds waste like cache bloat or retry tax, applies the fix, and tracks what it actually saved. Everything runs on your machine: no account, no uploads. MIT-licensed and genuinely free, used by 150k+ developers across the world.
CodeBurn is a free, local-first tool that tracks AI coding token usage and cost across 40 tools (Claude Code, Cursor, Codex, Copilot, Gemini and more). Break spend down by model, project, and task. A privacy-first ccusage alternative. 100% local, open source.
You used to find out at the end of the month. Now the number sits next to your clock all day, above every window, and one click opens the whole bill. The day's spend sits next to your clock. No dashboard to open, no tab to find. Plan usage metered live for every agent, with time remaining on each window. Per agent totals from today to lifetime, local or combined across your machines. Spend split by activity: coding, debugging, feature work, with turns and 1-shot rates. Native Swift. Reads local session files only. Nothing leaves your Mac. On Linux, the same number lives in your GNOME top bar. The bill stops being one number and becomes a map: which model, which project, which session, and…from codeburn.app
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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