Qwen Decision 27B noncausal LoRA vs amos-1-medium
Qwen Decision 27B noncausal LoRA and amos-1-medium have no measured difference in accuracy, calibration or cost in our data yet.
| Spec | Qwen Decision 27B noncausal LoRA | amos-1-medium |
|---|---|---|
| Provider | jsaurabh | Scira (mukaddamzaid) |
| Decision Index score | 58.5 | — |
| Calibration error (ECE) | 0.051 | — |
| Median latency (p50) | 127 ms | — |
| Cost per 1,000 decisions | — | — |
| Parameters | 28B | — |
| 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 Qwen Decision 27B noncausal LoRA or amos-1-medium 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, Qwen Decision 27B noncausal LoRA or amos-1-medium?
No calibration difference between Qwen Decision 27B noncausal LoRA and amos-1-medium is recorded yet.
Is Qwen Decision 27B noncausal LoRA or amos-1-medium 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.