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What each one decides, how well calibrated it is, how fast it answers and what it costs to pull. Up to 4 at a time; the better value in each row is marked.
| Property | fastino-labs/gliner2-5-decide | aac6fef/laya-mlx |
|---|---|---|
| Summary | Fastino's open-weight decision model. A DeBERTa-v3-large encoder that scores label sets supplied at runtime, answers single-label, multi-label, yes/no and ordinal questions in one pass, and extracts spans and relations. | Native MLX FP16 conversion of Laya for Apple silicon. The same ModernBERT-large encoder, decision transformer and heads, running in MLX with no PyTorch; the checkpoint Laya Studio fine-tunes from. |
| Decides | choice, score, noul, classify, extract, route | choice, score, noul |
| Architecture | gliner2 | laya |
| Fine-tuned from | fastino/gliner2-large-v1 | convai-innovations/laya |
| License | apache-2.0 | apache-2.0 |
| Availability | Open weights + hosted API | Open weights |
| Hosted by | Fastino | — |
| Input price | — | — |
| Decision accuracy | 60.2% | — |
| Calibration error | — | — |
| Valid action rate | — | — |
| Median latency | 38.3 ms | — |
| p95 latency | — | — |
| Evaluation suite | Fastino fast-decisions suite (17 datasets) | — |
| Latest version | 2026.09.25 | 2026.09 |
| Variants | encoder_config | encoder, tokenizer, LICENSE, NOTICE |
| Size of latest version | 1.8 GB | 807.0 MB |
| Files | 6 | 10 |
| Downloads | 0 | 0 |
| Stars | 0 | 0 |
| Tags | system-one, encoder, deberta, extraction, gliner, 340m | system-one, mlx, apple-silicon, modernbert, conversion, 421m |
| Updated | Sep 26, 2026 | Sep 26, 2026 |