ScaleDown Classify-1 vs Kev 4B r10
ScaleDown Classify-1 is cheaper per 1,000 decisions. Choose on whichever of accuracy, calibration and cost matters most for your decisions.
| Spec | ScaleDown Classify-1 | Kev 4B r10 |
|---|---|---|
| Provider | ScaleDown | Jared Palmer |
| Decision Index score | — | 39.5 |
| Calibration error (ECE) | — | 0.032 |
| Median latency (p50) | — | 59 ms |
| Cost per 1,000 decisions | $0.0080 | $0.0084 |
| Parameters | — | 5B |
| 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 Kev 4B r10 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 Kev 4B r10?
No calibration difference between ScaleDown Classify-1 and Kev 4B r10 is recorded yet.
Is ScaleDown Classify-1 or Kev 4B r10 cheaper per 1,000 decisions?
ScaleDown Classify-1 is cheaper: about $0.0080 vs $0.0084 per 1,000 decisions at 200 input tokens each.
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.