A 0.6B replica of the System One idea trained on game environments. A Qwen3-0.6B backbone with an attention-based Choice head that scores a dynamic candidate set for Maze, Snake, ViZDoom and position prediction, shipped with its full training pipeline.
One of the earliest Jev-shaped scorers. A sequence-classification head on Qwen3.5-4B-Base scores each (state, question, option) triple and softmaxes per question. Non-commercial licence.
Decides
choice, noul, score
choice, score, noul, classify
Architecture
nanojev
scorer
Fine-tuned from
qwen/qwen3-0.6b
qwen/qwen3.5-4b-base
License
mit
cc-by-nc-4.0
Availability
Open weights
Open weights
Hosted by
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Input price
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Decision accuracy
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70.7%
Calibration error
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0.044
Valid action rate
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Median latency
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112 ms
p95 latency
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Evaluation suite
Figures are from each model’s manifest; accuracy and latency are what the publishers report, on their own suites and hardware. Add a third model.
Questions
What is the difference between nanojev and system-one-qwen3-5-4b-scorer?
nanojev is from TianyuCodings and system-one-qwen3-5-4b-scorer from pngwn. Both have open weights you can download and run. Both answer choice, noul and score questions. Only system-one-qwen3-5-4b-scorer answers classify. nanojev is the smaller model, at 600M parameters to 4.0B. nanojev is licensed mit; system-one-qwen3-5-4b-scorer, cc-by-nc-4.0.
Which is more accurate, nanojev or system-one-qwen3-5-4b-scorer?
Only system-one-qwen3-5-4b-scorer publishes an accuracy figure (70.7% on author-reported); nanojev does not, so there is no comparison to make without your own test.
Which is cheaper, nanojev or system-one-qwen3-5-4b-scorer?
nanojev: Free (open weights). system-one-qwen3-5-4b-scorer: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run nanojev or system-one-qwen3-5-4b-scorer locally?
Yes, both: systemone pull tianyu-codings/nanojev and systemone pull pngwn/system-one-qwen3-5-4b-scorer download the weights.
