decision-machine-1 vs GLiNER2.5-Decide
decision-machine-1 and GLiNER2.5-Decide have no measured difference in accuracy, calibration or cost in our data yet.
| Spec | decision-machine-1 | GLiNER2.5-Decide |
|---|---|---|
| Provider | milliseconds.ai | Fastino |
| Decision Index score | — | 10.1 |
| Calibration error (ECE) | — | 0.088 |
| Median latency (p50) | — | 23 ms |
| Cost per 1,000 decisions | — | — |
| Parameters | — | 486M |
| Open weights | No | Yes |
| Question types | Choice (one of N options), Yes / no, Extraction (typed spans) | Choice (one of N options), Score (ordered rubric), Yes / no, Extraction (typed spans) |
| Mechanism | Hosted API | Span encoder (GLiNER family) |
| License | proprietary | apache-2.0 |
FAQ
Is decision-machine-1 or GLiNER2.5-Decide more accurate?
At least one of the two has no Jev Decision Index score yet, so their accuracy cannot be compared here.
Which is better calibrated, decision-machine-1 or GLiNER2.5-Decide?
No calibration difference between decision-machine-1 and GLiNER2.5-Decide is recorded yet.
Is decision-machine-1 or GLiNER2.5-Decide cheaper per 1,000 decisions?
A hosted price is not recorded for both models; open-weight models cost the compute you run them on.
Cost per 1,000 decisions assumes 200 input tokens per decision. Pricing is indicative — confirm with the provider before production use. Highlighted values indicate the better figure for that row.