whatmodel.sh / decision / laya (DecisionBench 1c5edc17)

laya (DecisionBench 1c5edc17) is an open-weights decision model from ConvAI Innovations. Its published size is 0.42129383B parameters. Licence: apache-2.0.

Catalogue identity notes

DecisionBench v1 comparison: convaiinnovations/laya, revision 1c5edc17a7acd8701df6fc341c0d179f1c62c982; decision-model; adapter laya-hf; probability source native-decisions-probability-distribution. Kept separate from newer or unpinned Decision Index recipes; standard prompt, not compact. No unverified OpenRouter price imported. Current repository metadata checked separately; an unpinned alias is not evidence that today’s weights reproduce this historical run. Reviewed Ollaya local route added 2026-10-31: laya:en, manifest c305a9276531a47000bf93559d2c94f1ed6cbb67055c9151084682dad7655e9d, matching the independent accuracy-run manifest. Native family implementation; published runtime precision label F16. Memory is measured peak GPU increase (1654 MiB, rounded upward to 1.7 GiB) on RTX 5090 during the short five-question triage workload, not download size or a maximum-context guarantee. Runtime installation is required; no fresh execution performed here. Historical benchmark adapter and input protocol still vary by result.

Model information sources

· Weights licence ↗ · Parameter count ↗

Published served parameter count; not a RAM or download-size measurement.

24.5±1.4#329 of 355 decision modelsfrom 41 benchmark results across 2 sources

$ how it compares

The decision models ranked either side of laya (DecisionBench 1c5edc17), out of 357 with a score, then more from ConvAI Innovations.

#modelscorewhereRAMreleased
329Von 1.3 wfzyx25±1model files2026-09-28
330Bosun v3.1 0.6B LoRA Hanno Labs25±1model files2026-09-22
331laya (DecisionBench 1c5edc17) ConvAI Innovations25±1local~1.7GB
332kev-0.5b (DecisionBench 9ce2fd39) Jared Palmer24±2model files
333Crivo-17M tardellirs24±1model files
more from ConvAI Innovations
315laya-typed-decisions (DecisionBench bc76315b) ConvAI Innovations29±2model files
340Laya ConvAI Innovations21±1model files

see all decision models · find the ones that fit your machine

$ what it's good at

knowledge & reasoning▁▂▂▂▂▃▃▅▅▆█▂ #193 of 263 · 11% of its score · 9 tests

Beats StartLux-Decision v1.1 0.8B, Sieve 2B v3, OneJev1.6-0.8B here, though they rank higher overall.

testresultvs the others in its rundifficultycountswhy
Ollaya · BoolQ83.7% ✎▁··▃▃▁▄▁▃█▇▄ beats 11/25easy · avg 84%▇ 3.5%at its level
Ollaya · PubMedQA50.0% ✎▃▂▃▃·▂▃▃▆█▆▂ beats 5/25easy · avg 69%▇ 3.2%at its level
Ollaya · SQuAD 2 answerability61.9% ✎▁▃▃▁▇█▃▃▄▃·▁ beats 1/25easy · avg 80%▇ 1.6%blunt · at its level
Ollaya · VitaminC verification79.0% ✎▁···▃·▄█▃··▁ beats 18/25easy · avg 78%▇ 1.4%blunt · at its level
Ollaya · MultiNLI87.6% ✎▂··▄██▂▆▆█▆▂ beats 13/25very easy · avg 87%▇ 1.0%blunt
system1bench · boolq84.6% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with
system1bench · xnli en86.0% ✎█··········█ beats 1/1—not counted yet: no other model in the same run to compare it with
system1bench · xnli zh61.5% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with
1 more test
testresultvs the others in its rundifficultycountswhy
system1bench · turtlebench42.6% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with
workflows▁▁▁▃▁▂▂▆█▄▁▁ #102 of 114 · 88% of its score · 58 tests

Trails GLiNER2.5-Decide here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
DecisionBench v1 · action selection (all-request accuracy) submitted25.7% ✎▂▁▂▃▄▃▁▁▂█▇▄ beats 11/56medium · avg 51%▇▇▇▇ 10%typical
DecisionBench v1 · routing (all-request accuracy) submitted30.0% ✎▁▁▁▁▃▂▁▁▁▁▃█ beats 12/56medium · avg 64%▇▇▇ 8.4%sharp · at its level
DecisionBench v1 · completion assessment (all-request accuracy) submitted35.0% ✎▁▁▃▃▄·▂▁▁▆█▂ beats 5/56very easy · avg 86%▇▇▇ 7.6%sharp · at its level
DecisionBench v1 · bounded extraction (all-request accuracy) submitted24.8% ✎▃▃▂·▁▁▁▁▁▁█▅ beats 7/56very easy · avg 86%▇▇▇ 6.3%sharp · at its level · noisy
DecisionBench v1 · navigation (all-request accuracy) submitted15.0% ✎▁▁·▃▁▁▁▁▁▁▃█ beats 6/56medium · avg 58%▇▇ 5.2%sharp
DecisionBench v1 · triage (all-request accuracy) submitted41.0% ✎▁·▁·▂▃▄▃▂█▄▂ beats 10/56easy · avg 78%▇▇ 4.9%sharp · at its level
Ollaya · Typed decisions test35.8% ✎▄·▂▆▄▄▂·▄█▆▆ beats 1/22medium · avg 64%▇▇ 4.6%at its level
Ollaya · MASSIVE German intent40.9% ✎▁····▃·▂▃▆█▃ beats 1/23easy · avg 84%▇▇ 4.3%sharp · at its level
50 more tests
testresultvs the others in its rundifficultycountswhy
Ollaya · PAWS paraphrase57.6% ✎▂▃▂▂·▃█▆·▂·▁ beats 2/25easy · avg 81%▇▇ 4.2%at its level
DecisionBench v1 · verification (all-request accuracy) submitted42.5% ✎▁▁▅▁▃▂▂▁▁▇▇█ beats 16/56medium · avg 56%▇▇ 4.1%blunt · at its level
DecisionBench v1 · record classification (all-request accuracy) submitted23.0% ✎▃▂▁▂▃▂▄▁▃▆██ beats 13/56medium · avg 39%▇▇ 4.0%typical
Ollaya · Aegis 2 safety42.8% ✎▃·▁▁▂·▃▃▂█▃▁ beats 1/25easy · avg 77%▇ 3.1%at its level
DecisionBench v1 · content classification (all-request accuracy) submitted49.0% ✎▁····▁▁▁▁▃▁█ beats 12/56easy · avg 73%▇ 3.0%at its level
DecisionBench v1 · document record classification (all-request accuracy) submitted32.5% ✎▂▂·▁▂▄▃▆▄█▁▁ beats 14/56medium · avg 46%▇ 2.6%at its level
Ollaya · MASSIVE English intent68.6% ✎▁·······▃▃█▃ beats 1/23very easy · avg 86%▇ 2.3%at its level · noisy
DecisionBench v1 · rubric scoring prioritization (all-request accuracy) submitted32.8% ✎▁▁▅▅▃▃▅█▃▃·▁ beats 19/56medium · avg 45%▇ 2.2%at its level
DecisionBench v1 · review scoring (all-request accuracy) submitted22.0% ✎▁······▃▃▅▇█ beats 4/56medium · avg 52%▇ 1.6%at its level
Ollaya · SummEval consistency4.2% ✎▁·▃▁··▁▁▁▁▄█ beats 1/25easy · avg 75%▇ 1.5%sharp · at its level · noisy
Ollaya · SummEval relevance6.3% ✎▃··▁▂▁▅··▃██ beats 0/25medium · avg 41%▇ 1.4%typical
DecisionBench v1 · risk scoring (all-request accuracy) submitted42.0% ✎▁▁·▁▂▃▁▃▃█▇▃ beats 10/56medium · avg 62%▇ 1.4%blunt · at its level
Ollaya · HelpSteer 2 scoring15.7% ✎▃▁··▁·▁▃▇█▅▄ beats 0/23medium · avg 38%▇ 0.7%blunt · at its level
DecisionBench v1 · reasoning (all-request accuracy) submitted40.8% ✎▂·▁▁▆█▅▃▃▂▁▁ beats 21/56medium · avg 52%▇ 0.7%at its level
DecisionBench v1 · retrieval verification (all-request accuracy) submitted50.7% ✎█▁▂▁▁▁▁▁▂▅▁▁ beats 11/56easy · avg 74%▇ 0.7%at its level · noisy
DecisionBench v1 · retrieval ranking (all-request accuracy) submitted4.0% ✎▁▁·▁▃▂▃▂▃▁▁█ beats 5/56medium · avg 35%▇ 0.6%noisy
DecisionBench v1 · document workflows (all-request accuracy) submitted50.5% ✎█▄▃▁▁▃▂▂▁·▁▁ beats 20/56easy · avg 66%▇ 0.6%blunt · at its level
DecisionBench v1 · target selection (all-request accuracy) submitted7.0% ✎▁▁·▁▁▁▃▁▂▁▁█ beats 10/56hard · avg 29%▇ 0.6%noisy
DecisionBench v1 · safety gating (all-request accuracy) submitted60.0% ✎▂·····▆█▂▂▄▇ beats 23/56easy · avg 77%▇ 0.5%at its level · noisy
DecisionBench v1 · guardrails moderation (all-request accuracy) submitted39.3% ✎▁▁▁▂▆▃▃█···▁ beats 22/56medium · avg 52%▇ 0.3%blunt · at its level · noisy
DecisionBench v1 · semantic filtering (all-request accuracy) submitted53.0% ✎▁·▁▁·▁▁█▂▃█▂ beats 16/56easy · avg 71%▇ 0.2%blunt · at its level · noisy
DecisionBench v1 · content moderation (all-request accuracy) submitted49.0% ✎▁····▃▅▃▂▂·█ beats 10/56easy · avg 82%▇ 0.2%at its level · noisy
Ollaya · Civil Comments93.7% ✎▂▂▂·▂▅▅▆▃▅·█ beats 23/23very easy · avg 86%▇ 0.2%blunt · noisy
DecisionBench v1 · context management (all-request accuracy) submitted51.0% ✎▁·····▁▇▆▁█▃ beats 9/56easy · avg 73%▇ 0.1%blunt · at its level · noisy
DecisionBench v1 · document classification (all-request accuracy) submitted4.0% ✎▂▁·▂▁▃▁▄▁▂▂█ beats 11/56hard · avg 21%▇ 0.1%blunt · noisy
DecisionBench v1 · entity alignment (all-request accuracy) submitted19.0% ✎▁·▁▄▇▄▅▄▂▁▄█ beats 10/56easy · avg 66%▇ 0.1%at its level · noisy
DecisionBench v1 · function agent skill routing (all-request accuracy) submitted22.8% ✎▃▃▄▅▆▂▅▄▃▄█▃ beats 9/56easy · avg 68%▇ 0.1%blunt · at its level · noisy
DecisionBench v1 · routing triage (all-request accuracy) submitted18.4% ✎█▁···▃·▂▆▅▂▂ beats 20/56medium · avg 42%▇ 0.0%blunt · at its level · noisy
system1bench · ag news94.3% ✎█··········█ beats 1/1—not counted yet: no other model in the same run to compare it with
system1bench · emotion59.1% ✎█··········█ beats 1/1—not counted yet: no other model in the same run to compare it with
system1bench · banking7755.3% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with
system1bench · sst534.6% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with
system1bench · massive en54.1% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with
system1bench · massive zh30.4% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with
system1bench · prompt injections70.7% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with
system1bench · typed decisions36.4% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with
system1bench · jevbench original70.8% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with
system1bench · jevbench easy95.8% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with
system1bench · jevbench hard29.7% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with
system1bench · reflexbench reflex-public-choice-v159.0% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with
system1bench · jev laya triage62.5% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with
system1bench · jev laya moderation67.8% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with
system1bench · jev laya routing64.2% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with
system1bench · jev laya claims90.0% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with
system1bench · jev laya reviews70.7% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with
system1bench · jev laya guard60.6% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with
system1bench · jev laya multilingual57.8% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with
system1bench · jev laya needle50.2% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with
system1bench · clinc150 oos55.7% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with
system1bench · aegis2 prompt49.6% ✎█··········█ beats 0/1—not counted yet: no other model in the same run to compare it with

$ where to run it

Other ways to run it

  1. Run it as published · needs 1.7 GB, NVIDIA only · from github.com/ollaya-dev
    ollaya run laya:en --preset triage "The customer requests a refund."

Download model files ↗
Published model files verified. This is the revision recorded by the benchmark. A matching Ollaya runtime manifest and published short-workload GPU memory measurement were reviewed separately; see local variants and identity_note. The command was not executed in this review. Source · checked 2026-10-31.

Model repository and documentation: huggingface.co/convaiinnovations ↗

$ how the score was worked out · Hanno Labs DecisionBench v1 r… 66%, Ollaya · original runs 33%

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

sourceresultsshare of the scorelicence
Hanno Labs DecisionBench v1 reviewed results · submitted; independent execution unverified27CC0 1.0
Ollaya · original runs14Apache-2.0
prior · pull toward the middle
weighted average= 24.5

not counted (26)

CYMCharming · system1benchsystem1bench · ag news [correct]94.3%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · emotion [correct]59.1%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · banking77 [correct]55.3%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · boolq [correct]84.6%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · sst5 [correct]34.6%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · xnli en [correct]86.0%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · xnli zh [correct]61.5%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · massive en [correct]54.1%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · massive zh [correct]30.4%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · prompt injections [correct]70.7%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · typed decisions [correct]36.4%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · jevbench original [correct]70.8%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · jevbench easy [correct]95.8%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · jevbench hard [correct]29.7%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · reflexbench reflex-public-choice-v1 [correct]59.0%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · jev laya triage [correct]62.5%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · jev laya moderation [correct]67.8%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · jev laya routing [correct]64.2%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · jev laya claims [correct]90.0%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · jev laya reviews [correct]70.7%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · jev laya guard [correct]60.6%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · jev laya multilingual [correct]57.8%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · jev laya needle [correct]50.2%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · clinc150 oos [correct]55.7%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · turtlebench [correct]42.6%fewer than three models have this test yet, or this source ran it for this model alone
CYMCharming · system1benchsystem1bench · aegis2 prompt [correct]49.6%fewer than three models have this test yet, or this source ran it for this model alone

$ 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