Featherless AI's open server that turns a stock Hugging Face language model into a typed-decision endpoint. It reads the next-token logits for each question and builds the Choice, Score or Noul answer itself; no classifier head is trained and no JSON is generated.
meraGPT's hosted decision model (state-decider-1). Answers yes/no, choice and rubric-score questions over one state as calibrated distributions in a single pass, on the System One schema, so the typesafe-sdk works by changing its base URL.
Decides
choice, score, noul, classify, route
choice, score, noul, classify, route
Architecture
simple-jev
state-decider
Fine-tuned from
google/gemma-4-26b-a4b-it
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License
apache-2.0
proprietary
Availability
Open weights + hosted API
Hosted API
Hosted by
Featherless AI
meraGPT
Input price
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$0.030/MTok
Decision accuracy
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76.8%
Calibration error
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Valid action rate
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Median latency
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p95 latency
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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 simple-jev and state-decider-1?
simple-jev is from Featherless AI and state-decider-1 from meraGPT. simple-jev has open weights and a hosted API; state-decider-1 is only available as a hosted API. Both answer choice, score, noul, classify and route questions. simple-jev is licensed apache-2.0; state-decider-1, proprietary.
Which is more accurate, simple-jev or state-decider-1?
Only state-decider-1 publishes an accuracy figure (76.8% on typed-decisions benchmark (400 cases, 2,000 decisions; teacher-ensemble references), single run); simple-jev does not, so there is no comparison to make without your own test.
Which is cheaper, simple-jev or state-decider-1?
simple-jev: Hosted, price not published, or free to self-host. state-decider-1: $0.03 / $0 per 1M. Open weights cost nothing per call beyond your own hardware.
Can I run simple-jev or state-decider-1 locally?
simple-jev yes — systemone pull featherless-ai/simple-jev downloads its weights. The other is only served as a hosted API.
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Evaluation suite
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typed-decisions benchmark (400 cases, 2,000 decisions; teacher-ensemble references), single run
