Baseten: Mammoth 1 (free) vs vLLM-SR d3 (27B)
Baseten: Mammoth 1 (free) and vLLM-SR d3 (27B) have no measured difference in accuracy, calibration or cost in our data yet.
| Spec | Baseten: Mammoth 1 (free) | vLLM-SR d3 (27B) |
|---|---|---|
| Provider | Baseten | vLLM Semantic Router |
| Decision Index score | — | 67.2 |
| Calibration error (ECE) | — | 0.043 |
| Median latency (p50) | — | 97 ms |
| Cost per 1,000 decisions | Free | — |
| Parameters | — | 26B |
| 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 Baseten: Mammoth 1 (free) or vLLM-SR d3 (27B) 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, Baseten: Mammoth 1 (free) or vLLM-SR d3 (27B)?
No calibration difference between Baseten: Mammoth 1 (free) and vLLM-SR d3 (27B) is recorded yet.
Is Baseten: Mammoth 1 (free) or vLLM-SR d3 (27B) 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.