Categoryexternal
MeasureChance-adjusted skill points
Tasks6 component benchmarks
DifficultyVaries by task and supplied answer options
Fastino reports GLiDE at 60.9 skill points on Retrieval and Classification in its Decision Index 0.2.1 run. The comparison quotes the published Jev 1.13.0 reference.
Retrieval and Classification (Fastino report) ranking
1 model with a published Retrieval and Classification (Fastino report) value, ordered by that value, highest first. Models the source has not scored on this benchmark are not listed — they are unmeasured, not last.
Models ranked by their published Retrieval and Classification (Fastino report) value| Rank | Model | Provider | Chance-adjusted skill points |
|---|
| 1 | FAGLiDE | Fastino | 60.9 |
Evidence key: Observed
Rows are ordered by the value Fastino GLiDE launch and Decision Index results published, highest first. The source does not state whether a higher value is the better result, so this page does not either: for a benchmark that measures a rate of failure, read the table from the bottom.
About Retrieval and Classification (Fastino report)
What the benchmark measures and how its value is published, from the source’s own record.
What is Retrieval and Classification (Fastino report)?
Retrieval and Classification (Fastino report) is an external benchmark published by Fastino GLiDE launch and Decision Index results. Fastino reports GLiDE at 60.9 skill points on Retrieval and Classification in its Decision Index 0.2.1 run. The comparison quotes the published Jev 1.13.0 reference. Its evaluation set is described by the source as 6 component benchmarks. The source rates its difficulty as varies by task and supplied answer options.
How is Retrieval and Classification (Fastino report) scored?
Each model's result is published by Fastino GLiDE launch and Decision Index results as chance-adjusted skill points. ModelScale prints that value to 1 decimal place, exactly as published, and never converts or rescales it. This page ranks the 1 model that carry a published value, highest value first; a model the source never scored is left out rather than ranked at zero. The source does not state whether a higher value is the better result, so neither does this page.
ModelScale