LuminaBench
Finance benchmark / Vals AI

ClaimBench

Lumina VerifiedLumina checked the published sources, versions, model labels, score extraction and conversion. External evaluations were run by their publishers; Lumina has not independently rerun or reproduced them.

Accuracy

Version 1-updated-2026-10-23Verified 6 November 202625 published resultsOfficial source

ClaimBench

LuminaBench
Show
20 of 25 models · best variant per model
03006009001,2001,059Claude Haiku 5.5Max1,059anthropic/claude-opus-5-5Max1,059anthropic/claude-sonnet-5-5Max1,059d1-ultra1,059openai/gpt-6.1-solMax1,054Decider V1.21,047Drex Max1,047openai/gpt-6-lunaMax1,046Mercury Decide1,041Decider V1.1 27B1,040d11,033Microsoft-Decision-11,031Jev 1.141,031Drex v1.51,025Jev 1.13.01,020Drex v2.01,015GPT-6 Luna Decisions1,010Decider Flash V1.2989Clef979Solar Decide

Lumina Score vs Cost per Task

Published per-test USD and Duration/Test retain their native definitions. Tokens use published averages or original aggregate counts divided by token_tasks_measured; total = input + output, with cache and reasoning subsets retained separately rather than counted twice. No task values are inferred from token prices or compute budgets.

LuminaBench
15 of 25 families
Lower resource use and higher score (green); higher resource use and lower score (red). Guides split at the visible selection’s medians.$0.0001$0.0003$0.001$0.003$0.01$0.03$0.18009001,0001,100Cost per task · USD (log scale)Lumina Scored1-ultraClaude Haiku 5.5anthropic/claude-opus-5-5anthropic/claude-sonnet-5-5Mercury DecideDecider V1.2

Lumina Score vs Time per Task

Published per-test USD and Duration/Test retain their native definitions. Tokens use published averages or original aggregate counts divided by token_tasks_measured; total = input + output, with cache and reasoning subsets retained separately rather than counted twice. No task values are inferred from token prices or compute budgets.

LuminaBench
15 of 25 families
Lower resource use and higher score (green); higher resource use and lower score (red). Guides split at the visible selection’s medians.0.313108009001,0001,100Time per task · s (log scale)Lumina Scored1-ultraClaude Haiku 5.5Jev 1.14Decider V1.1 27Bd1Microsoft-Decision-1

Published per-test USD and Duration/Test retain their native definitions. Tokens use published averages or original aggregate counts divided by token_tasks_measured; total = input + output, with cache and reasoning subsets retained separately rather than counted twice. No task values are inferred from token prices or compute budgets. Missing metrics are omitted from their graph; quality scores remain available.

Results table

Method & coverage

Text claims and 10-K excerpts classified using three labels; native probability outputs. Main accuracy retained separately from cascade/threshold alternatives.

Published per-test USD and Duration/Test retain their native definitions. Tokens use published averages or original aggregate counts divided by token_tasks_measured; total = input + output, with cache and reasoning subsets retained separately rather than counted twice. No task values are inferred from token prices or compute budgets.

How the Lumina conversion works

1,000 + 75 × ((original score − 95.86128) / 5.277118278151439). The result is rounded once. Scores may tie.

Frozen initial observed text-only cohort; one mean per exact publisher release/API, balancing repeated settings/routes within that release. Original score and protocol remain separate. No inferred variants or future refitting.

Calibration
vals-claimbench-z75-v1 · experimental
Reference mean
95.86128
Population SD
5.277118278151439
Coverage
Standalone benchmark.
Identity, exclusions & attribution

Text claims and 10-K excerpts classified using three labels; native probability outputs. Main accuracy retained separately from cascade/threshold alternatives.

Publisher standard errors retained; no confidence level or interval inferred. Aggregate reporting scope is recorded in the current source-specific publication review.

Standalone text benchmark; no new combined index. Source identity/effort/protocol qualifications remain in Data and CSV.

All published reasoning settings, including Claude Max, are included by default. Display labels use Low and xHigh; source labels remain in the retained records.

Official source · Publication terms / evidence

Publisher terms. Scores and resource figures are attributed to the original publisher.