# PR#23: the dashboard shows input and output tokens per model

> **WARNING:** This document describes only the change applied in this PR.
> It may already be outdated once the next PR is merged.
> Historic PR documentation is not maintained along with new PRs; treat it as a snapshot.

## The Problem

The choice of the LLM depends on how the costs split into input and output.
On 23 runs of the earlier reviews, Claude Sonnet 5.5 read about 96 input tokens per output token,
so its input price decided about 94 % of the costs: in the median run, 58400 input tokens at 2 USD per million
cost about 0.117 USD, 740 output tokens at 10 USD per million about 0.007 USD.
GPT-6 Astra wrote far more output.

The statistics service stores only costs, so this ratio can only be measured by hand from CI artifacts,
which Werkator prunes after a while.
The usage record of every run already holds the token counts.

## Non-Goals

- No cost split into input and output in USD: the service knows no prices, and they change.
- No change of the command-line tool or of the usage record that it sends; only the service stores more of it.

## The Scenarios

### Feature: the dashboard shows the tokens per model

#### Scenario#23.01: the service keeps the token counts of a run

So that the ratio of input and output tokens can be measured over all runs.

- **Given** a run reports 58000 prompt tokens, 740 completion tokens and 1200 Jev input tokens
- **When** someone with a read token asks for the statistics
- **Then** the sums per model hold 58000 LLM input tokens, 740 LLM output tokens and 1200 Jev input tokens

##### Verified by

- [UsageApiIntegrationTest: token counts are summed per model](../../server/src/test/kotlin/de/hoennig/werkrevisor/server/UsageApiIntegrationTest.kt)

#### Scenario#23.02: the table per model shows the ratio of input to output

So that the operator sees at a glance which price decides the costs of a model.

- **Given** the reviews of the last 30 days used two models
- **When** someone opens the dashboard with a read token
- **Then** the table "Last 30 days by model" shows per model the input tokens, the output tokens and the ratio, e.g. "113 : 1"

##### Verified by

- manual check in a browser, see [Measurement](#measurement)

#### Scenario#23.03: a database of an earlier version gets the new columns

So that an update keeps the stored records.

- **Given** a database written by werkrevisor 0.18.1
- **When** the service of this version starts
- **Then** the stored records stay, with no token counts

##### Verified by

- [UsageApiIntegrationTest: a database of an earlier version gets the token columns](../../server/src/test/kotlin/de/hoennig/werkrevisor/server/UsageApiIntegrationTest.kt)

## The Solution

- The service stores `prompt_tokens`, `completion_tokens` and the sum of the three Jev input token counts;
  it adds the columns to an existing database at the start.
- Each sum holds `llmInputTokens`, `llmOutputTokens` and `jevInputTokens`;
  the Web Component shows them in the table per model, with the ratio.
- werkrevisor 0.18.2.

## Measurement

On 2026-10-06, the dashboard ran locally with 187 usage records of earlier runs.
The table "Last 30 days by model" showed 113 : 1 for Claude Sonnet 5.5, 24 : 1 for GPT-6 Astra,
19 : 1 for Gemini 3.8 Flash and 1 : 1 for DeepSeek V4 Pro, each in one line without wrapping.

## Prerequisite PRs

- PR#22: estimated costs marked, LLM and Jev listed apart.