# Fastino Labs: gliner2-5-decide

> 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.

- Page: https://systemonemodels.ai/fastino-labs/gliner2-5-decide
- API: https://api.systemonemodels.ai/v1/models/fastino-labs/gliner2-5-decide
- Download: `pip install systemonemodels && systemone pull fastino-labs/gliner2-5-decide`

## Facts

| | |
|---|---|
| Maker | Fastino Labs (https://systemonemodels.ai/fastino-labs) |
| Decides | choice, score, noul, classify, extract, route |
| Architecture | gliner2 |
| Base model | fastino/gliner2-large-v1 |
| Parameters | 340M |
| Licence | apache-2.0 |
| Availability | Open weights + hosted API |
| Released | 2026-09-24 |
| Latest version | 2026.09.25 |

## Hosted API

- Provider: Fastino (https://agent.fastino.ai)

- Input: — · Output: —

## Reported evaluation

Suite: Fastino fast-decisions suite (17 datasets). Numbers are the publisher's own.

- Decision accuracy: 60.2%

- Median latency: 38.3 ms

## Model card

<!-- generated by scripts/seed_catalog.py; edit content/models/catalog.yaml -->

# GLiNER2.5-Decide

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.

GLiNER2.5-Decide joins classification, extraction and cross-decision rules in one constrained decode; nothing is generated. Fastino reports 60.2% on its own fast-decisions suite of 17 datasets (the launch post says 60.1%) and 38 ms median on a V100, 167 ms on a 48-vCPU CPU. The card says 340M parameters; the safetensors header counts 486M. Two Apache-2.0 siblings share the recipe: GLiNER2.5-Decide-1B (59.6%) and GLiNER2.5-multi-Decide (287M, multilingual, 56.7%). It loads through the gliner2 package rather than the /v1/systemone wire format, and is also served through Fastino's API.

## What it decides

- **choice** — picks one option from a set
- **score** — places the input on an ordered scale
- **noul** — answers a yes/no question with one calibrated probability
- **classify** — assigns a category from a fixed taxonomy
- **extract** — pulls spans or fields out of the input
- **route** — sends the input to one of several destinations

## At a glance

| | |
|---|---|
| Parameters | 340M |
| Base model | `fastino/gliner2-large-v1` |
| Maker | Fastino Labs |
| Released | 2026-09-24 |
| License | apache-2.0 |
| Reported accuracy | 60.2% |
| Reported latency | 38 ms p50 on V100; 43–47 ms on T4/L4/A100; 167 ms on a 48-vCPU CPU |

## Hosted API

Served by **Fastino**. [Get access](https://agent.fastino.ai).

## Get the weights

```bash
pip install systemonemodels
systemone pull fastino-labs/gliner2-5-decide
```

The files are served from the maker's Hugging Face repository, [`fastino/GLiNER2.5-Decide`](https://huggingface.co/fastino/GLiNER2.5-Decide), and verified against the checksums recorded here.

## Read more

- [Launch post](https://fastino.ai/blog/gliner-2-5-decide-open-weight-decision-model)
- [Weights on Hugging Face](https://huggingface.co/fastino/GLiNER2.5-Decide)
- [GLiNER2.5-Decide-1B](https://huggingface.co/fastino/GLiNER2.5-Decide-1B)
- [GLiNER2.5-multi-Decide](https://huggingface.co/fastino/GLiNER2.5-multi-Decide)

---

*This page was opened by System One for Fastino Labs, who can claim the organisation and take it over at any time.*

---

From System One Models — https://systemonemodels.ai/ · every System One model: https://systemonemodels.ai/system-one-models