whatmodel.sh / decision / Open-Jev-2B (DecisionBench 0c7aa498)

Open-Jev-2B (DecisionBench 0c7aa498)

+ contribute

Open-Jev-2B (DecisionBench 0c7aa498) is an open-weights decision model from ZefanCai, released 20 September 2026. Licence: apache-2.0.

Catalogue identity notes

DecisionBench v1 comparison: ZefanCai/Open-Jev-2B, revision 0c7aa498b1627be8da4acf34c863ff0ee0a92785; decision-model; adapter jev-compatible-server-v1-overlong-input-truncation; probability source native_scalar_logits_temperature_softmax. Kept separate from newer or unpinned Decision Index recipes; standard prompt, not compact. No unverified runtime or OpenRouter price imported. Current repository metadata checked separately; an unpinned alias is not evidence that today’s weights reproduce this historical run.

Model information sources

Release date ↗ · Weights licence ↗

47.9±1.6#224 of 355 decision modelsfrom 27 benchmark results across 1 source

$ how it compares

The decision models ranked either side of Open-Jev-2B (DecisionBench 0c7aa498), out of 357 with a score, then more from ZefanCai.

#	model	score	where	released
224	razorback16 diffgemma (decision readout) vllm-project	48±1	source code
225	Interfaze lev Qwen3.5-4B LoRA Interfaze	48±1	model files
226	Open-Jev-2B (DecisionBench 0c7aa498) ZefanCai	48±2	model files	2026-09-20
227	Valen-4B Valen	48±1	model files
228	RSI-Jev v5.0 VL 3B shgao	48±1	model files	2026-10
	more from ZefanCai
153	Open-Jev-9B (DecisionBench 47e96688) ZefanCai	56±2	model files	2026-09-20

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

$ what it's good at

workflows▁▁▁▂▁▂▃▆█▄▁▁ #78 of 114 · 99% of its score · 27 tests

Trails GLiClass v4 edge (0.4B) here, though they rank lower overall.

test	result	vs the others in its run	difficulty	counts	why
DecisionBench v1 · action selection (all-request accuracy) submitted	42.3% ✎	▂▁▂▃▄▃▃▁▂█▇▄ beats 23/56	medium · avg 51%	▇▇▇▇▇▇▇ 19%	at its level
DecisionBench v1 · routing (all-request accuracy) submitted	64.3% ✎	▁▁▁▁▂▂▁▁▁▃▃█ beats 26/56	medium · avg 64%	▇▇▇▇▇▇ 14%	sharp · at its level
DecisionBench v1 · navigation (all-request accuracy) submitted	69.0% ✎	▁▁·▃▁▁▁▁▁▁▃█ beats 33/56	medium · avg 58%	▇▇▇▇ 11%	sharp · at its level
DecisionBench v1 · record classification (all-request accuracy) submitted	41.0% ✎	▃▂▁▂▂▂▄▁▃▆██ beats 28/56	medium · avg 39%	▇▇▇ 7.9%	at its level
DecisionBench v1 · verification (all-request accuracy) submitted	53.0% ✎	▁▁▅▁▃▂▂▁▃▇▇█ beats 24/56	medium · avg 56%	▇▇ 5.9%	blunt · at its level
DecisionBench v1 · completion assessment (all-request accuracy) submitted	86.0% ✎	▁▁▂▃▄·▂▁▃▆█▂ beats 25/56	very easy · avg 86%	▇▇ 5.7%	sharp
DecisionBench v1 · bounded extraction (all-request accuracy) submitted	88.7% ✎	▃▃▂·▁▁▁▁▃▁█▅ beats 24/56	very easy · avg 86%	▇▇ 5.5%	sharp · noisy
DecisionBench v1 · triage (all-request accuracy) submitted	59.0% ✎	▁·▁·▂▃▄▃▂█▄▂ beats 19/56	easy · avg 78%	▇▇ 5.1%	sharp

19 more tests

test	result	vs the others in its run	difficulty	counts	why
DecisionBench v1 · document record classification (all-request accuracy) submitted	43.8% ✎	▂▂·▁▂▄▃▆▄█▁▁ beats 26/56	medium · avg 46%	▇▇ 4.6%	at its level
DecisionBench v1 · rubric scoring prioritization (all-request accuracy) submitted	38.3% ✎	▁▁▅▅▃▃▅█▃▃·▁ beats 24/56	medium · avg 45%	▇▇ 3.9%	at its level
DecisionBench v1 · content classification (all-request accuracy) submitted	77.0% ✎	▁····▁▁▁▁▁▁█ beats 28/56	easy · avg 73%	▇ 3.6%	at its level
DecisionBench v1 · review scoring (all-request accuracy) submitted	49.0% ✎	▁······▂▃▅▇█ beats 26/56	medium · avg 52%	▇ 2.6%	at its level
DecisionBench v1 · retrieval ranking (all-request accuracy) submitted	49.0% ✎	▁▁·▁▁▂▃▂▃▁▃█ beats 35/56	medium · avg 35%	▇ 1.9%	at its level · noisy
DecisionBench v1 · risk scoring (all-request accuracy) submitted	64.0% ✎	▁▁·▁▂▂▁▃▃█▇▃ beats 33/56	medium · avg 62%	▇ 1.8%	blunt · at its level
DecisionBench v1 · target selection (all-request accuracy) submitted	38.0% ✎	▁▁·▁▁▁▃▁▂▁▃█ beats 33/56	hard · avg 29%	▇ 1.7%	at its level · noisy
DecisionBench v1 · reasoning (all-request accuracy) submitted	39.8% ✎	▂·▁▁▆█▅▃▃▂▁▁ beats 18/56	medium · avg 52%	▇ 1.1%	at its level
DecisionBench v1 · retrieval verification (all-request accuracy) submitted	51.2% ✎	█▁▂▁▁▁▁▁▂▅▁▁ beats 15/56	easy · avg 74%	▇ 0.8%	at its level · noisy
DecisionBench v1 · document workflows (all-request accuracy) submitted	57.0% ✎	█▄▃▁▁▃▂▂▁·▁▁ beats 29/56	easy · avg 66%	▇ 0.7%	blunt · at its level
DecisionBench v1 · guardrails moderation (all-request accuracy) submitted	38.3% ✎	▁▁▁▂▆▃▃█···▁ beats 13/56	medium · avg 52%	▇ 0.5%	blunt · at its level · noisy
DecisionBench v1 · safety gating (all-request accuracy) submitted	58.0% ✎	▂·····▆█▂▂▄▇ beats 21/56	easy · avg 77%	▇ 0.5%	noisy
DecisionBench v1 · semantic filtering (all-request accuracy) submitted	57.0% ✎	▁·▁▁·▁▁█▂▃█▂ beats 20/56	easy · avg 71%	▇ 0.3%	blunt · at its level · noisy
DecisionBench v1 · document classification (all-request accuracy) submitted	35.0% ✎	▂▁·▂▁▁▁▄▁▂▂█ beats 49/56	hard · avg 21%	▇ 0.3%	blunt · noisy
DecisionBench v1 · content moderation (all-request accuracy) submitted	81.0% ✎	▁····▃▅▃▂▂·█ beats 25/56	easy · avg 82%	▇ 0.2%	noisy
DecisionBench v1 · context management (all-request accuracy) submitted	62.0% ✎	▁·····▁▇▆▁█▃ beats 21/56	easy · avg 73%	▇ 0.2%	blunt · at its level · noisy
DecisionBench v1 · entity alignment (all-request accuracy) submitted	97.6% ✎	▁·▁▄▇▄▅▄▂▁▄█ beats 40/56	easy · avg 66%	▇ 0.2%	at its level · noisy
DecisionBench v1 · function agent skill routing (all-request accuracy) submitted	94.4% ✎	▃▃▄▅▆▂▅▄▃▄█▃ beats 40/56	easy · avg 68%	▇ 0.1%	blunt · at its level · noisy
DecisionBench v1 · routing triage (all-request accuracy) submitted	60.5% ✎	█▁···▁·▂▆▅▂▂ beats 38/56	medium · avg 42%	▇ 0.0%	blunt · at its level · noisy

$ where to run it

Download model files ↗
Published model files verified. Includes adapters or readout weights; follow the model documentation for the required base model. This is the revision recorded by the benchmark. A local run command and hardware requirements have not been verified for this entry. Source · checked 2026-10-31.

Model repository and documentation: huggingface.co/ZefanCai ↗

$ how the score was worked out · Hanno Labs DecisionBench v1 r… 99%

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	licence
Hanno Labs DecisionBench v1 reviewed results · submitted; independent execution unverified	27	▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 99%	CC0 1.0
prior · pull toward the middle		▇ 1%
weighted average		= 47.9

$ improve this page

Update model information Add a place to run it Add a test result Propose a benchmark Correct a benchmark score Edit data on GitHub

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 2026-11-03 02:37 UTC · sources and licences · json