Methodology

Data sources and scoring

We use licensed and public benchmark evidence for two distinct publication types: task-specific predicted-fit composites and source-native direct benchmark outcomes. Their scales stay separate. Source-listed identities, known configurations, uncertainty treatment, missing data and attribution remain inspectable.

Active sources

EQ-Bench 3

Public benchmark signals used in the SpringPrompt predicted-fit beta.

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Attribution: EQ-Bench 3 by Samuel Paech / EQ-bench
Source snapshot fetched: 2026-07-16
Configurations: 33

Source methodology ↗ Source terms ↗

The benchmark numbers are source-listed or deterministically derived from the attributed release. SpringPrompt attribution and interpretation do not imply that a source endorses our task mappings, rankings or operational overlays.

EQ-Bench Creative Writing v3

Public benchmark signals used in the SpringPrompt predicted-fit beta.

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Attribution: Creative Writing v3 by Samuel Paech / EQ-bench
Source snapshot fetched: 2026-07-16
Configurations: 33

Source methodology ↗ Source terms ↗

LMArena Leaderboard Dataset

Public benchmark signals used in the SpringPrompt predicted-fit beta.

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Attribution: Contains data from the Arena Leaderboard Dataset by Arena, licensed under CC BY 4.0
Source snapshot fetched: 2026-07-16
Configurations: 33

Source methodology ↗ Source terms ↗

UGI Leaderboard

Public benchmark signals used in the SpringPrompt predicted-fit beta.

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Attribution: UGI Leaderboard by DontPlanToEnd, via Hugging Face Spaces
Source snapshot fetched: 2026-07-16
Configurations: 33

Source methodology ↗ Source terms ↗

Structured Output Benchmark (SOB)

Direct structured-output outcome score and uncertainty rank range.

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Attribution: Structured Output Benchmark (SOB) by Interfaze / JigsawStack, Inc. (MIT License)
Source release date: 2026-07-02
Configurations: 35

Source methodology ↗ Source terms ↗

Artificial Analysis

Operational price and output-throughput metadata only; not a predicted-fit input.

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Attribution: Operational price and performance data sourced from Artificial Analysis
Source snapshot fetched: 2026-07-16
Configurations: 22

Source methodology ↗

Verification and current model availability are not exposed by this API.

Model identity: conservative by design

Every source-listed model variant is retained, even when Spring Prompt cannot run it.
A source-listed variant may link to our runnable catalog only through an authoritative identifier that is unique on both sides or a human-reviewed alias decision. Those are different evidence paths and are labelled separately.
Provider, revision, reasoning effort, and service tier are score-affecting identity fields when the source supplies them; published values cannot be discarded.
Name similarity creates a review suggestion only. It never makes a result rankable and never selects the highest-scoring variant.

Published task rankings

We publish only reviewed task mappings or direct benchmarks with a defensible target match. Unsupported categories receive no score.

Predictive public beta: Email Writing and Business Writing only. These two tasks are non-strict predictions assembled from several attributed benchmark sources, and they are the only task scores entering the overall Writing-fit standing. They are not task-success percentages or fresh direct model runs.

Business Writing

2026-07-16-business-candidate-v6

Predicted ability to produce clear, coherent and audience-appropriate business prose such as briefs, updates, proposals and memos.

Coverage floor: 55%
Signal groups: 3+
Lineages: 3+

Email Writing

2026-07-16-business-candidate-v6

Predicted ability to write accurate, audience-aware, appropriately toned and action-oriented business, sales and support emails.

Coverage floor: 55%
Signal groups: 3+
Lineages: 3+

Direct benchmark publication: Structured Output Reliability. This preserves the source-native direct score, point order and marginal bootstrap overlap rank range. It is not blended with the two predictive Writing tasks and does not enter the overall Writing-fit standing.

Structured Output Reliability

Structured Output Benchmark Overall · 35 model families

Directly measured ability to return accurate values in the requested structured schema across the benchmark's evaluated text, image and audio modalities.

100 × evaluated-modality coverage × equal-weight mean of the seven publisher-defined unified component outcomes.

Overall exclusion: The source-native direct score is not on the same calibrated scale as SpringPrompt predicted-fit task scores; cross-task scale compatibility has not been established.

Rank ranges use overlap of marginal record-cluster bootstrap intervals for Overall; simultaneous rank confidence is not claimed.

Published ranking safeguards

Predicted fit is a relative within-task estimate, not a task-success percentage, probability, guarantee, or cross-category score.
Evidence coverage is displayed separately from performance; missing signals are not treated as model failures.
Only model families meeting the published coverage, independent-signal-group, and evidence-lineage floors enter the provisional order.
The order is explicitly non-strict. Small score differences should be treated as the same performance band.
Product-family identity matching does not prove that a model is runnable through SpringPrompt, so no runnable model link is invented.
Artificial Analysis price and output-throughput metadata is joined only by an exact reviewed family key, remains visibly tied to its representative configuration, and never changes predicted fit.
Structured Output retains the publisher-defined Overall formula and source-native 0–100 scale; it is never relabelled as predicted fit or a task-success guarantee.
Its 95% Overall intervals use record-cluster bootstrap resampling with component covariance preserved. Overlap produces a marginal rank range, not simultaneous confidence for the full rank vector.
Structured Output is explicitly excluded from the overall Writing-fit standing because scale compatibility with predicted-fit scores has not been established.
ROASBench and BulletBench remain Spring Prompt-run focused benchmarks and are labelled separately from external-source composites.