💸 Track Your Savings — the local dashboard that makes local-first feel real

The on-device savings dashboard. The comparison is what a month of Diapason usage would have cost on the cloud — measured per-query, not estimated. Nothing is uploaded.

Diapason tracks every inference call you make — the tokens, the latency, the GPU energy — and computes what that same call would have cost on OpenAI, Anthropic, Google, and Bedrock. Those numbers stay on your machine.

My current month is roughly:

Local inference cost	$0.00
Cloud-equivalent cost	$342.18 (Claude Sonnet 4.6 baseline)
Energy used	1.4 kWh (~12¢ of grid power)
Prompts sent to a third party	0

The dollar number is the hook. The bottom row is the actual reason I run Diapason.

Why it's nice

• You can see what each query costs you. Not estimated, not "roughly" — measured. Watt-hours per token, FLOPs per token, latency. Every primitive in Diapason treats compute cost as a first-class quantity alongside accuracy.
• It makes "local-first" stop being abstract. Watching a bar chart accumulate $X a week that didn't leave your hands is a different kind of motivating than "your data is private" claims that you can't verify.
• Privacy stops being an act of faith. Every prompt I send to Diapason can be traced through the codebase to local-only paths. No "cloud failover" hiding behind a switch.

How I set this up

You don't, really — metering is on by default and stays local. Every diapason ask, diapason serve request, and channel-routed message is recorded by the telemetry system.

→ Telemetry overview — what's measured, where it's stored, and how to inspect it yourself with diapason telemetry.