# Are there open-source System One models?

Yes. A handful of open-source reproductions match Jev's `/v1/systemone` wire format among the alternatives systemonemodels.org lists, and most of them say outright that they haven't kept the one property that actually defines a System One model: a probability that tracks accuracy. Systemonemodels.org describes OpenDecision's confidence as concentration, not correctness, a paraphrase of OpenDecision's own README, which says only to treat the model's scores as uncalibrated, and mini-jev calls its number "ranking with confidence gap, not calibrated probabilities."

Von, a non-autoregressive local model built to the same spec, is more direct about the tradeoff than most: its own README reports 72.0% macro accuracy against Jev's 96.6% on a 49-task suite, while beating Jev on a fast, reactive game-playing benchmark where raw speed matters more than calibrated judgment.

None of that makes an open alternative useless, it makes the calibration claim something to check rather than assume. [Measuring any grader's accuracy runs the same way](/answers/graders/how-do-you-measure-whether-a-grader-itself-is-accurate): against a labeled set with a known right answer, not against a vendor's own README, before trusting an open model's confidence the way TypeSafe's own training method earns Jev's.

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Sources:
- Von (GitHub), an open-source System One decision model: https://github.com/wfzyx/von (fetched 2026-09-21)
- systemonemodels.org, Jev alternatives: open-source reproductions, local models and classifiers: https://systemonemodels.org/examples/alternatives/ (fetched 2026-09-21)

Source: https://tessary.ai/answers/system-one-models/are-there-open-source-system-one-models
More on System one models: https://tessary.ai/answers/system-one-models
From Tessary, agent reliability for AI agents in production: https://tessary.ai