amos-1-medium vs Darwin-27B-ZTC
amos-1-medium and Darwin-27B-ZTC have no measured difference in accuracy, calibration or cost in our data yet.
| Spec | amos-1-medium | Darwin-27B-ZTC |
|---|---|---|
| Provider | Scira (mukaddamzaid) | FINAL_Bench |
| Decision Index score | — | 62.5 |
| Calibration error (ECE) | — | 0.045 |
| Median latency (p50) | — | 104 ms |
| Cost per 1,000 decisions | — | — |
| Parameters | — | 26B |
| Open weights | Yes | Yes |
| 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 | Decoder LM with a decision readout |
| License | apache-2.0 | apache-2.0 |
FAQ
Is amos-1-medium or Darwin-27B-ZTC 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, amos-1-medium or Darwin-27B-ZTC?
No calibration difference between amos-1-medium and Darwin-27B-ZTC is recorded yet.
Is amos-1-medium or Darwin-27B-ZTC 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.