ScaleDown Classify-1 vs frontier-infra Jebadiah 27B v2.1
ScaleDown Classify-1 and frontier-infra Jebadiah 27B v2.1 have no measured difference in accuracy, calibration or cost in our data yet.
| Spec | ScaleDown Classify-1 | frontier-infra Jebadiah 27B v2.1 |
|---|---|---|
| Provider | ScaleDown | Frontier Infra |
| Decision Index score | — | 55.9 |
| Calibration error (ECE) | — | 0.061 |
| Median latency (p50) | — | 110 ms |
| Cost per 1,000 decisions | $0.0080 | — |
| Parameters | — | 28B |
| Open weights | No | Yes |
| Question types | Choice (one of N options), Score (ordered rubric), Yes / no | Choice (one of N options), Score (ordered rubric), Yes / no |
| Mechanism | Encoder classifier | Decoder LM with a decision readout |
| License | proprietary | apache-2.0 |
FAQ
Is ScaleDown Classify-1 or frontier-infra Jebadiah 27B v2.1 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, ScaleDown Classify-1 or frontier-infra Jebadiah 27B v2.1?
No calibration difference between ScaleDown Classify-1 and frontier-infra Jebadiah 27B v2.1 is recorded yet.
Is ScaleDown Classify-1 or frontier-infra Jebadiah 27B v2.1 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.