vLLM-SR Decision 2.0 Vega 27B vs Perplexity: Decider Latest
vLLM-SR Decision 2.0 Vega 27B and Perplexity: Decider Latest have no measured difference in accuracy, calibration or cost in our data yet.
| Spec | vLLM-SR Decision 2.0 Vega 27B | Perplexity: Decider Latest |
|---|---|---|
| Provider | vLLM Semantic Router | Perplexity |
| Decision Index score | 58.0 | — |
| Calibration error (ECE) | 0.086 | — |
| Median latency (p50) | 120 ms | — |
| Cost per 1,000 decisions | — | $0.0040 |
| 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 Perplexity: Decider Latest 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 Perplexity: Decider Latest?
No calibration difference between vLLM-SR Decision 2.0 Vega 27B and Perplexity: Decider Latest is recorded yet.
Is vLLM-SR Decision 2.0 Vega 27B or Perplexity: Decider Latest 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.