# scar-ai: vera

> A 1.9B-parameter decision model from the scar-ai account: a Qwen3.5-2B backbone with its own decision head reads a state and typed questions (choice, score, yes/no) and returns a probability per option in one forward pass, generating no text. 8K context, Apache-2.0.

- Page: https://systemonemodels.ai/scar-ai/vera
- API: https://api.systemonemodels.ai/v1/models/scar-ai/vera
- Download: `pip install systemonemodels && systemone pull scar-ai/vera`

## Facts

| | |
|---|---|
| Maker | scar-ai (https://systemonemodels.ai/scar-ai) |
| Decides | choice, score, noul |
| Architecture | vera |
| Base model | qwen/qwen3.5-2b |
| Parameters | 1.9B |
| Context | 8K tokens |
| Licence | apache-2.0 |
| Availability | Open weights |
| Released | 2026-10-03 |
| Latest version | 2026.09 |

## Reported evaluation

Suite: JevBench public set (231 items), the maker's own run. Numbers are the publisher's own.

- Decision accuracy: 77.9%
- Calibration error (ECE): 0.098
- Median latency: 42 ms

## Model card

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# vera-core

A 1.9B-parameter decision model from the scar-ai account: a Qwen3.5-2B backbone with its own decision head reads a state and typed questions (choice, score, yes/no) and returns a probability per option in one forward pass, generating no text. 8K context, Apache-2.0.

The Qwen3.5-2B backbone gets a purpose-built head that scores each question's options, and the whole stack is fully fine-tuned on decision data the card does not describe. Choice takes 2 to 255 options, score 2 to 10 levels. It speaks Jev's /v1/systemone shape through the maker's vera-serve (no auth, binds 127.0.0.1); it needs custom code or the vera-s1 package, and Apple MPS is not supported. The maker presents it as a generalist base to fine-tune. On JevBench's 231 public items (a third-party suite; the maintainers have not ranked it) the maker's own run gives 77.9% (easy 100, original 93.1, hard 58.6) with ECE 0.098; that is the only calibration evidence. Sibling vera-spark (about 638M, ModernBERT-large with MoE layers, same interface) scores 68.8% in the same run.

## 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 probability

## At a glance

| | |
|---|---|
| Parameters | 1.9B |
| Base model | `Qwen/Qwen3.5-2B` |
| Maker | scar-ai |
| Released | 2026-10-03 |
| License | apache-2.0 |
| Reported accuracy | 77.9% |
| Reported latency | 41 to 44 ms median per question on an MI300X, batch of one |

## Get the weights

```bash
pip install systemonemodels
systemone pull scar-ai/vera
```

The files are served from the maker's Hugging Face repository, [`scar-ai/vera-core`](https://huggingface.co/scar-ai/vera-core), and verified against the checksums recorded here.

## Read more

- [Model card](https://huggingface.co/scar-ai/vera-core)
- [vera-spark](https://huggingface.co/scar-ai/vera-spark)

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