Kev 27B vs Celeris-1 Decision
Kev 27B and Celeris-1 Decision have no measured difference in accuracy, calibration or cost in our data yet.
| Spec | Kev 27B | Celeris-1 Decision |
|---|---|---|
| Provider | Jared Palmer | Celeris |
| Decision Index score | 58.8 | — |
| Calibration error (ECE) | 0.022 | — |
| Median latency (p50) | 135 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 | Diffusion LM |
| License | apache-2.0 | proprietary |
FAQ
Is Kev 27B or Celeris-1 Decision 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 27B or Celeris-1 Decision?
No calibration difference between Kev 27B and Celeris-1 Decision is recorded yet.
Is Kev 27B or Celeris-1 Decision 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.