Diffusion Jev vs GLiNER2.5-Decide
Diffusion Jev and GLiNER2.5-Decide have no measured difference in accuracy, calibration or cost in our data yet.
| Spec | Diffusion Jev | GLiNER2.5-Decide |
|---|---|---|
| Provider | — | 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 | Diffusion LM | Span encoder (GLiNER family) |
| License | — | apache-2.0 |
FAQ
Is Diffusion Jev 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, Diffusion Jev or GLiNER2.5-Decide?
No calibration difference between Diffusion Jev and GLiNER2.5-Decide is recorded yet.
Is Diffusion Jev 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.