LuminaBench
Legal benchmark / Vals AI

Immigration

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-2026-10-28Verified 6 November 202625 published resultsOfficial source

Immigration

LuminaBench
Show
20 of 25 models · best variant per model
03006009001,2001,162Claude Fable 5.1Max1,104Claude Opus 5.5Max1,087Wonder FullMax1,068Qwen 3.8 Max1,059WonderMax1,048Claude Sonnet 5.5Max1,035Kimi K3Max1,032Gemini 4 ArgonHigh1,032Grok 4.7xHigh1,028GPT-6.1 SolMax1,025GPT-6 AstraMax1,022MiMo V2.6 Pro1,009GLM 5.3Max1,005Muse Spark 1.2xHigh995Grok 4.6High989DeepSeek V4.1 FlashMax978Muse Spark 1.3xHigh977Muse Spark 1.3 MaxMax956Mistral Large 4 PreviewHigh950Gemini 3.8 FlashHigh

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.$0.03$0.1$0.3$1$38009001,0001,1001,200Cost per task · USD (log scale)Lumina ScoreClaude Fable 5.1MiMo V2.6 ProClaude Opus 5.5Wonder FullQwen 3.8 MaxWonder

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.13108009001,0001,1001,200Time per task · min (log scale)Lumina ScoreClaude Fable 5.1Muse Spark 1.2Claude Opus 5.5Qwen 3.8 MaxWonderKimi K3

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 immigration-law questions and expert-authored rubrics; per-question rubric accuracy. No scanned document input protocol.

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 − 66.24) / 4.271119956170747). 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-immigrationbench-z75-v1 · experimental
Reference mean
66.24
Population SD
4.271119956170747
Coverage
Standalone benchmark.
Identity, exclusions & attribution

Text immigration-law questions and expert-authored rubrics; per-question rubric accuracy. No scanned document input protocol.

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.