GLiClass multilang ultra vs ScaleDown Classify-1
GLiClass multilang ultra and ScaleDown Classify-1 have no measured difference in accuracy, calibration or cost in our data yet.
| Spec | GLiClass multilang ultra | ScaleDown Classify-1 |
|---|---|---|
| Provider | Knowledgator | ScaleDown |
| Decision Index score | — | — |
| Calibration error (ECE) | — | — |
| Median latency (p50) | — | — |
| Cost per 1,000 decisions | — | $0.0080 |
| Parameters | — | — |
| Open weights | Yes | No |
| Question types | Choice (one of N options), Yes / no | Choice (one of N options), Score (ordered rubric), Yes / no |
| Mechanism | Encoder classifier | Encoder classifier |
| License | Apache 2.0 | proprietary |
FAQ
Is GLiClass multilang ultra or ScaleDown Classify-1 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, GLiClass multilang ultra or ScaleDown Classify-1?
No calibration difference between GLiClass multilang ultra and ScaleDown Classify-1 is recorded yet.
Is GLiClass multilang ultra or ScaleDown Classify-1 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.