LibertAI released Deem, an open-weight model positioned as an alternative to Jev, built on Qwen3.5-9B with a smaller 0.8B variant. It trails Jev on hard benchmarks but arrives early in a new model category, and the small version runs on CPU for local tinkering.
A developer released OpenJudgement-4B-Preview, an experimental Qwen-based model fine-tuned on custom datasets for classification, scoring, and true/false judgments. It scores answer options directly rather than generating responses token by token, with Python formatting results into JSON with probabilities. The early preview is unfinished and positioned as a not-yet-Jev-level alternative, with the author soliciting feedback on failure cases.
A developer released OpenJudgement-4B-Preview, an experimental Qwen-based model fine-tuned on custom datasets for classification, scoring, and true/false judgments. It scores answer options directly rather than generating responses token by token, with Python formatting results into JSON with probabilities. The early preview is unfinished and positioned as a not-yet-Jev-level alternative, with the author soliciting feedback on failure cases.
Reddit users report that Alibaba's Qwen team has published a docs page for a model called decision-model-preview, described as a competitor to Jev. The page appeared without any announcement, and no open weights are available yet.
Reddit users report that Alibaba's Qwen team has published a docs page for a model called decision-model-preview, described as a competitor to Jev. The page appeared without any announcement, and no open weights are available yet.
jevos is an open-source alternative to Jev: you send a text and a yes/no question and get an answer in one forward pass without generating text. It runs on a laptop CPU, making cheap yes/no classification over documents feasible. Aimed at developers who want fast, local rule-checking instead of full LLM generation.
jevos is an open-source alternative to Jev: you send a text and a yes/no question and get an answer in one forward pass without generating text. It runs on a laptop CPU, making cheap yes/no classification over documents feasible. Aimed at developers who want fast, local rule-checking instead of full LLM generation.
A practitioner evaluated open-source SystemOne models against Jev using DecideBench on a production-like dataset. No open-source model beat Jev, but several came close, with Imajev-4B reaching 95% accuracy as the cheapest model above 90%. The findings help teams pick cost-effective Jev substitutes.
A practitioner evaluated open-source SystemOne models against Jev using DecideBench on a production-like dataset. No open-source model beat Jev, but several came close, with Imajev-4B reaching 95% accuracy as the cheapest model above 90%. The findings help teams pick cost-effective Jev substitutes.
Kev is a family of small Jev-architecture decision models (0.8B, 4B, 9B) built on Qwen3.5 and released under Apache-2.0 with training code and frozen eval suites. The 9B model runs in bf16 on a 32GB Mac, and the models are API-compatible with TypeSafe's System One, so its Python SDK works against a local Kev server unchanged. The release targets LLM-as-judge eval pipelines, and the web playground demonstrates option-order bias that judge models commonly exhibit.
Kev is a family of small Jev-architecture decision models (0.8B, 4B, 9B) built on Qwen3.5 and released under Apache-2.0 with training code and frozen eval suites. The 9B model runs in bf16 on a 32GB Mac, and the models are API-compatible with TypeSafe's System One, so its Python SDK works against a local Kev server unchanged. The release targets LLM-as-judge eval pipelines, and the web playground demonstrates option-order bias that judge models commonly exhibit.