reflex 4B vs GLiNER2.5-Decide
reflex 4B and GLiNER2.5-Decide have no measured difference in accuracy, calibration or cost in our data yet.
| Spec | reflex 4B | GLiNER2.5-Decide |
|---|---|---|
| Provider | kshetrajna12 | 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 | Yes | Yes |
| Question types | Choice (one of N options), Score (ordered rubric), Yes / no | Choice (one of N options), Score (ordered rubric), Yes / no, Extraction (typed spans) |
| Mechanism | Decoder LM with a decision readout | Span encoder (GLiNER family) |
| License | — | apache-2.0 |
FAQ
Is reflex 4B 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, reflex 4B or GLiNER2.5-Decide?
No calibration difference between reflex 4B and GLiNER2.5-Decide is recorded yet.
Is reflex 4B 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.