Mira-v1
Fast, honest, open typed decisions
What is this?
Mira turns state + typed questions → probability distributions in a single
forward pass. No text generation. Ask choice, score, or noul questions —
alone or batched — and get calibrated probabilities, confidence, and an
abstain signal your code can branch on.
Evaluation
Measured on commodity CPU (i5-1335U), one harness for every open model.
| Benchmark | Mira-v1 | Julia 1 | Jev |
|---|---|---|---|
| Typed decisions (2000) | 0.745 | 0.726 | 0.727 |
| ECE (15-bin) | 0.025 | 0.234 | — |
| Confident-error (≥0.9) | 0.006 | 0.234 | — |
| AG News (100) | 0.25 | 0.94 | 0.91 |
| Emotion (100) | 0.87 | 0.86 | 0.48 |
| Banking77 (100, native full-label) | 0.93 | 0.64 (72-label shortlist variant) | 0.87 |
| Short-query p50 | 30 ms | 321 ms | 70–500 ms API |
romanized Nepali, and code-mixed slices are Mira-first reporting no other small model publishes.
Limitations
Mira compares answers you provide. it cannot supply missing facts or do arithmetic. Severity direction and urgency separation are the softest slices. Past 20 options a two-stage shortlist narrows then decides (recall reported). Score the exact questions you plan to use before consequential actions. Training data is private; eval harness and predictions are public.