UsageTap Compress · measured prompts, modeled API spend

What compression saves—and what the answers retain

OriginalSelected compressionCompression fee

Quality alongside savings

BenchmarkMetricBefore scoreAfter scoreChangePairs / questions

Observed means on the sampled questions, with each metric kept separate. Repeated calls are not independent documents. Both compression and generation variation can affect score changes; this cohort does not establish broad quality equivalence.

Savings at other models’ API prices

Cost-only extrapolation from the same Terra prompt counts and observed output counts. No new model calls. These estimates do not measure Sol, Astra or Opus answer quality, latency, or tokenization; Claude’s actual tokenizer and responses can differ.

Published standard rates, USD per million tokens
ModelInputCached inputOutput
Projected before and after cost components

ModelBefore inputBefore outputBefore totalAfter inputAfter outputCompressionAfter totalNet savedSaved %

Context tokens

Proxy token counts; instructions and questions excluded.

API-equivalent cost

Matched answer calls; after includes the modeled compression fee.

Net savings by workload

After compression fees, under the current pricing scenario.

Answer scores across repeats

Official task metric; points are individual calls. Compare within each task.

Request-time estimate

Median Codex time plus recorded compression preparation time.

Input cost and output cost

API prompt scenario, with output usage measured by Codex.

Before and after: the cost ledger

InputPairsBefore APIAfter APICompressionAfter totalNet saved
Pricing, cache and compression assumptions

Cache reads, ordinary input and writes are disjoint input categories. A 30-minute write costs 1.25× input; a 12-hour write costs 2.5×. The long-context rate adjustment is applied above 272k input tokens. Scenario controls alter estimates only; they never alter measured results. Changing an early prompt prefix can reduce cache reuse.

Exact token and cost components
Input / stagePrompt inputOutputOrdinary input $Cached reads $Cache writes $Output $Compression $Total $

Before = ordinary input + cached reads + cache writes + output
After = ordinary input + cached reads + cache writes + output + compression charge
Net saving = Before − After

See what compression removes

Original input with removed text struck through. The answer checks below show the measured quality for these tasks.

Original, with removals

Compression details

Answers and quality checks

The published benchmark score is retained exactly. Normalized exact match is supplementary. Review the answers alongside the references: equivalent wording, digits versus spelled-out numbers, and extra detail can affect lexical scores.

Lexical scores can penalize digits versus spelled-out numbers, such as “3” versus “three”; inspect the actual answers and references below. Net cost differences also include variation in output length between calls.

VariantRepeatStatusActual answerOfficial scoreNormalized exact match

The cases are different tasks and use different metrics. Scores are never averaged across QA F1 and structured-data accuracy. Repeated calls share the same source input; they are not independent documents.

Experiment usage, provenance and limits

API dollar values are modeled estimates; answer generation ran through a Codex subscription. The primary cost comparison prices the application prompt and measured output, excluding Codex's agent instructions/tool envelope. The separate experiment diagnostic prices the complete CLI usage envelope. Output-token usage includes reasoning when reported; reasoning tokens are not added a second time. Prompt counts use a proxy tokenizer. Network and compression times vary with startup/cache conditions. Taxes, regional premiums, Batch/Flex discounts, Fast mode and unknown account-specific terms are excluded. The compression free allowance remaining is unknown; its toggle is a scenario.