OpenDecision
deepanwadhwa.github.io- Category
- Developer Tools
- Rank
- No. 3941Tools index
Previous survey · No. 3658 ·
- Pricing
- Open Source
- Type
- TOOL
- Use case
- Models: Train & Run
- Date
About
OpenDecision is an open-source, 400M-parameter zero-shot decision model built as a free alternative to commercial "Jev"-style decision systems, drawing on the author's prior work applying fine-tuned BERT and zero-shot models to healthcare insurance fraud audits. The author states it has an accuracy ceiling and warns against using it where wrong decisions carry real cost.
At a glance
OpenDecision runs local models that answer predefined questions about text, documents or images. It is worth evaluating if your application needs a structured decision, such as which queue receives a request, and you can test the possible answers in advance.
Good fit
Developers classifying inputs into known options who want local inference.
Consider something else when
Skip it if the task needs an open-ended answer or depends on details that do not fit the chosen input mode.
Start here
Read the routing example and create a few synthetic requests, including one with no suitable category. Check the selected value and decide when the application should ask a person.
Cost and requirements
The docs describe a local runtime with default models. Provision memory for your input length and concurrency, and check the selected model’s requirements.
Limits to know
The docs give different context limits for different question types. Long documents are split into passages and images are resized. Measure errors on inputs that resemble the ones your application will receive.
Related work
- Snap (alternative)
Sources checked 2026-11-05. Source-based assessment.
Why it made the leaderboard
Offers a free, tinkerable local decision model for low-stakes classification tasks, letting builders experiment with zero-shot decision-making without a commercial API.
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Editorially curated, with community endorsements as a secondary signal. Corrections welcome.