whatmodel.sh / decision / Laya (english) (JevBench mini)
Laya (english) (JevBench mini)
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Laya (english) (JevBench mini) is a source-available decision implementation from Convai Innovations.
Catalogue identity notes
JevBench 0.1.0 mini tested configuration laya: Encoder, option markers; base ModernBERT-large; readout one [MASK] marker per option. Separate identity because the report does not establish equivalence to the newer Decision Index checkpoint or serving recipe. No latency imported.
$ how it compares
The decision models ranked either side of Laya (english) (JevBench mini), out of 357 with a score, then more from Convai Innovations.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 295 | Mola-150M | 33±1 | model files | ||
| 296 |  DM-JEPA 1.1 | 33±1 | model files | ||
| 297 | Laya (english) (JevBench mini) | 33±2 | source code | ||
| 298 |  Kodiak v0.2 1B (accuracy) | 32±1 | model files | ||
| 299 | JEV FLAN-T5 Large public v2 (342M) | 32±1 | model files | ||
| more from Convai Innovations | |||||
| 291 | Laya (typed-decisions) (JevBench mini) | 33±2 | source code | ||
see all decision models · find the ones that fit your machine
$ what it's good at
consistency▃·▂▂·▅▃·▃▅▃█ #21 of 21 · 45% of its score · 5 tests
Trails Verdict 1.4 (JevBench mini) here, though they rank lower overall.
| test | result | vs the others in its run | counts |
|---|---|---|---|
| JevBench mini 0.1.0 · Probability measure coherence (pass rate) | 16.4% ✎ | ▄·▁·▃▃▁·▃▄▁█ beats 1/20 | 25% |
| JevBench mini 0.1.0 · Representation consistency (pass rate) | 52.5% ✎ | ▃·▂·▂▂▂▃▅▅▃█ beats 0/20 | 16% |
| JevBench mini 0.1.0 · Logical coherence (pass rate) | 67.9% ✎ | ▃·▃·█▅▅██▃█▅ beats 4/20 | 2.4% |
| JevBench mini 0.1.0 · Choice-set coherence (pass rate) | 45.8% ✎ | ▁▃▄█▄▄·····▄ beats 1/20 | 1.4% |
| JevBench mini 0.1.0 · Batch independence (pass rate) | 100.0% ✎ | ▁··········█ beats 2/20 | 0.0% |
other tests1 not in a task · 53% of its score
| test | result | vs the others in its run | counts |
|---|---|---|---|
| JevBench mini 0.1.0 · unchanged-answer accuracy | 70.8% ✎ | ▁·▂·▃···▂▂▁█ beats 3/20 | 53% |
$ where to run it
Implementation and setup instructions ↗
Published implementation and setup documentation verified. This entry describes a decision readout or evaluated configuration, not necessarily separate trained weights. Follow the referenced version and model settings; hardware compatibility has not been verified. Source · checked 2026-10-31.
Model repository and documentation: github.com/NandhaKishorM ↗
$ how the score was worked out · JevBench 0.1.0 mini evaluatio… 98%
Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works
| source | results | share of the score |
|---|---|---|
 JevBench 0.1.0 mini evaluation reports | 6 | 98% |
| prior · pull toward the middle | 2% | |
| weighted average | = 32.6 |
$ improve this page
Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.
data updated · sources and licences · json