LuminaBench
Science benchmark / Vals AI

MysteryMechanism

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-2026-10-29Verified 6 November 202629 published resultsOfficial source

MysteryMechanism

LuminaBench
Show
20 of 29 models · best variant per model
03006009001,2001,149GPT-6 AstraMax1,126Claude Opus 5.5Max1,123Claude Sonnet 5.5Max1,114Claude Fable 5.1Max1,105GPT-6.1 SolMax1,099Gemini 4 ArgonHigh1,046Claude Opus 5Max1,040Gemini 3.8 FlashHigh1,037Muse Spark 1.3 MaxMax1,032Claude Haiku 5.5Max1,032Wonder FullMax1,020GPT-5.6 SolMax1,002Grok 4.6High999GPT-6 SolMax981WonderMax973Kimi K3.1 ProMax967Grok 4.7xHigh958Qwen 3.8 Max952GLM 5.3Max949Ember-1

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 28 families
Lower resource use and higher score (green); higher resource use and lower score (red). Guides split at the visible selection’s medians.$0.3$1$39001,0001,1001,200Cost per task · USD (log scale)Lumina ScoreGPT-6.1 SolGPT-6 AstraClaude Opus 5.5Claude Fable 5.1Claude Sonnet 5.5Gemini 4 Argon

Lumina Score vs Tokens

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 28 families
300K1M3M9001,0001,1001,200Total tokens per task (log scale)Lumina ScoreGPT-6.1 SolGPT-6 AstraClaude Opus 5.5Claude Sonnet 5.5Claude Fable 5.1Gemini 4 Argon

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 29 families
Lower resource use and higher score (green); higher resource use and lower score (red). Guides split at the visible selection’s medians.102030409001,0001,1001,200Time per task · minLumina ScoreGPT-6 AstraGemini 3.8 FlashClaude Opus 5.5Claude Sonnet 5.5Claude Fable 5.1GPT-6.1 Sol

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

Active scientific discovery from text observations and controlled tool experiments; primary official overall task score.

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 − 30.319862068965516) / 11.459347245428939). 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-mysterymechanism-z75-v1 · experimental
Reference mean
30.319862068965516
Population SD
11.459347245428939
Coverage
Standalone benchmark.
Identity, exclusions & attribution

Active scientific discovery from text observations and controlled tool experiments; primary official overall task score.

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.