decisio v0.8.0 on gemma-4-31B-it vs GLiNER2.5-Decide
decisio v0.8.0 on gemma-4-31B-it and GLiNER2.5-Decide have no measured difference in accuracy, calibration or cost in our data yet.
| Spec | decisio v0.8.0 on gemma-4-31B-it | GLiNER2.5-Decide |
|---|---|---|
| Provider | aminry | 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 decisio v0.8.0 on gemma-4-31B-it 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, decisio v0.8.0 on gemma-4-31B-it or GLiNER2.5-Decide?
No calibration difference between decisio v0.8.0 on gemma-4-31B-it and GLiNER2.5-Decide is recorded yet.
Is decisio v0.8.0 on gemma-4-31B-it 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.