Kev 4B r10 vs amos-1-large
Kev 4B r10 and amos-1-large have no measured difference in accuracy, calibration or cost in our data yet.
| Spec | Kev 4B r10 | amos-1-large |
|---|---|---|
| Provider | Jared Palmer | Scira (mukaddamzaid) |
| Decision Index score | 39.5 | — |
| Calibration error (ECE) | 0.032 | — |
| Median latency (p50) | 59 ms | — |
| Cost per 1,000 decisions | $0.0084 | — |
| Parameters | 5B | — |
| 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 Kev 4B r10 or amos-1-large 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 4B r10 or amos-1-large?
No calibration difference between Kev 4B r10 and amos-1-large is recorded yet.
Is Kev 4B r10 or amos-1-large 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.