amos-1-large vs RLCD ModernBERT 151M
amos-1-large and RLCD ModernBERT 151M have no measured difference in accuracy, calibration or cost in our data yet.
| Spec | amos-1-large | RLCD ModernBERT 151M |
|---|---|---|
| Provider | Scira (mukaddamzaid) | heman10x |
| Decision Index score | — | 0.0 |
| Calibration error (ECE) | — | 0.154 |
| Median latency (p50) | — | 11 ms |
| Cost per 1,000 decisions | — | — |
| Parameters | — | 151M |
| Open weights | Yes | Yes |
| Question types | Choice (one of N options), Score (ordered rubric), Yes / no | Choice (one of N options), Yes / no |
| Mechanism | Decoder LM with a decision readout | Encoder classifier |
| License | apache-2.0 | Apache 2.0 |
FAQ
Is amos-1-large or RLCD ModernBERT 151M 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-large or RLCD ModernBERT 151M?
No calibration difference between amos-1-large and RLCD ModernBERT 151M is recorded yet.
Is amos-1-large or RLCD ModernBERT 151M 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.