vLLM-SR Decision 2.0 Vega 27B vs Nace.AI: Drex Max
vLLM-SR Decision 2.0 Vega 27B and Nace.AI: Drex Max have no measured difference in accuracy, calibration or cost in our data yet.
| Spec | vLLM-SR Decision 2.0 Vega 27B | Nace.AI: Drex Max |
|---|---|---|
| Provider | vLLM Semantic Router | Nace.AI |
| Decision Index score | 58.0 | — |
| Calibration error (ECE) | 0.086 | — |
| Median latency (p50) | 120 ms | — |
| Cost per 1,000 decisions | — | $0.012 |
| Parameters | 28B | — |
| Open weights | Yes | — |
| Question types | Choice (one of N options), Score (ordered rubric), Yes / no | — |
| Mechanism | Decoder LM with a decision readout | — |
| License | apache-2.0 | — |
FAQ
Is vLLM-SR Decision 2.0 Vega 27B or Nace.AI: Drex Max 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, vLLM-SR Decision 2.0 Vega 27B or Nace.AI: Drex Max?
No calibration difference between vLLM-SR Decision 2.0 Vega 27B and Nace.AI: Drex Max is recorded yet.
Is vLLM-SR Decision 2.0 Vega 27B or Nace.AI: Drex Max 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.