Telnyx's hosted decision models, in beta on Telnyx Inference. One request carries shared state and up to 64 typed questions (choice, yes/no noul, ordered score) and returns a probability per option, with no generated text, on a TypeSafe-compatible /v1/systemone route.
TokenRhythm's prefill-only decision model for agent workflows. Built on its NeoHorse-1-4B (a Qwen3.5-4B derivative), it predicts Choice, Noul and Score answers over application-defined options without generating text, with optional single-image input.
Decides
choice, score, noul, classify, route
choice, score, noul, classify, route
Architecture
telnyx-decision
neohorse
Fine-tuned from
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tokenrhythm/neohorse-1-4b
License
proprietary
apache-2.0
Availability
Hosted API
Open weights
Hosted by
Telnyx
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Input price
$0.035/MTok
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Decision accuracy
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75.3%
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 decision-flash and neohorse-jev?
decision-flash is from Telnyx and neohorse-jev from TokenRhythm. decision-flash is only available as a hosted API; neohorse-jev has open weights you can download and run. Both answer choice, score, noul, classify and route questions. decision-flash is licensed proprietary; neohorse-jev, apache-2.0.
Which is more accurate, decision-flash or neohorse-jev?
Only neohorse-jev publishes an accuracy figure (75.3% on JevBench public set (231 items), vLLM, maker's run); decision-flash does not, so there is no comparison to make without your own test.
Which is cheaper, decision-flash or neohorse-jev?
decision-flash: $0.035 / $0 per 1M. neohorse-jev: Free (open weights). Open weights cost nothing per call beyond your own hardware.
Can I run decision-flash or neohorse-jev locally?
neohorse-jev yes — systemone pull tokenrhythm/neohorse-jev downloads its weights. The other is only served as a hosted API.
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Evaluation suite
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JevBench public set (231 items), vLLM, maker's run
