
TokenBoard provides a public leaderboard that aggregates reported usage data from AI coding tools. Participants can sort rankings by total tokens, session volume, message counts, or projected expenses across different models and observed capabilities. The system relies on local collectors that read session telemetry from supported agents without transmitting any prompt text or generated output. This approach allows complete usage history to be reflected over time while preserving privacy for all reported activity. Additional views include yearly activity grids that highlight usage streaks and daily breakdowns of model distribution. Users may also generate compact shareable cards summarizing their totals and recent patterns for external posting.
Compare reported AI coding token totals, sessions, messages, estimated costs, and model mixes across users with sortable rankings and observed skills.
Visualize coding patterns through a yearly activity grid that highlights streaks, quiet periods, and daily session details including model breakdowns and token counts.
Generate shareable weekly cards showing usage totals, active days, and tool mix without exposing prompts, code, or raw session content.
Pricing model: Free. Plan details are indicative — check the site for current prices.
Our take: TokenBoard is a solid coding & dev choice. It's valued for compares usage across users without sharing sensitive data and visual activity insights and shareable cards. The main trade-off is initially limited to codex and claude code collectors. A good pick if you want capable AI without a high upfront cost.
No, TokenBoard stores only reported metrics and hashes while keeping prompt text, assistant output, and raw local session IDs on the user's device.
TokenBoard is a solid coding & dev choice. It's valued for compares usage across users without sharing sensitive data and visual activity insights and shareable cards. The main trade-off is initially limited to codex and claude code collectors. A good pick if you want capable AI without a high upfront cost.
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