Kev 9B v2 vs ScaleDown Classify-1
Kev 9B v2 and ScaleDown Classify-1 have no measured difference in accuracy, calibration or cost in our data yet.
| Spec | Kev 9B v2 | ScaleDown Classify-1 |
|---|---|---|
| Provider | Jared Palmer | ScaleDown |
| Decision Index score | 43.3 | — |
| Calibration error (ECE) | 0.045 | — |
| Median latency (p50) | 60 ms | — |
| Cost per 1,000 decisions | — | $0.0080 |
| Parameters | 10B | — |
| Open weights | Yes | No |
| Question types | Choice (one of N options), Score (ordered rubric), Yes / no | Choice (one of N options), Score (ordered rubric), Yes / no |
| Mechanism | Decoder LM with a decision readout | Encoder classifier |
| License | apache-2.0 | proprietary |
FAQ
Is Kev 9B v2 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, Kev 9B v2 or ScaleDown Classify-1?
No calibration difference between Kev 9B v2 and ScaleDown Classify-1 is recorded yet.
Is Kev 9B v2 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.