Fastino GLiDE vs amos-1-large
Fastino GLiDE and amos-1-large have no measured difference in accuracy, calibration or cost in our data yet.
| Spec | Fastino GLiDE | amos-1-large |
|---|---|---|
| Provider | Fastino | Scira (mukaddamzaid) |
| Decision Index score | 60.2 | — |
| Calibration error (ECE) | 0.040 | — |
| Median latency (p50) | 98 ms | — |
| Cost per 1,000 decisions | $0.030 | — |
| Parameters | 28B | — |
| Open weights | No | Yes |
| Question types | Choice (one of N options), Score (ordered rubric), Yes / no | Choice (one of N options), Score (ordered rubric), Yes / no |
| Mechanism | Hosted API | Decoder LM with a decision readout |
| License | proprietary | apache-2.0 |
FAQ
Is Fastino GLiDE 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, Fastino GLiDE or amos-1-large?
No calibration difference between Fastino GLiDE and amos-1-large is recorded yet.
Is Fastino GLiDE 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.