Solomon v1.1 vs ScaleDown Classify-1
Solomon v1.1 and ScaleDown Classify-1 have no measured difference in accuracy, calibration or cost in our data yet.
| Spec | Solomon v1.1 | ScaleDown Classify-1 |
|---|---|---|
| Provider | Doccy Health | ScaleDown |
| Decision Index score | 40.9 | — |
| Calibration error (ECE) | 0.081 | — |
| Median latency (p50) | 224 ms | — |
| Cost per 1,000 decisions | — | $0.0080 |
| Parameters | 28B | — |
| 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 Solomon v1.1 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, Solomon v1.1 or ScaleDown Classify-1?
No calibration difference between Solomon v1.1 and ScaleDown Classify-1 is recorded yet.
Is Solomon v1.1 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.