# EmpirioLabs AI: Open-Weight Models and Datasets
Source: https://savrn.com/model-publishers/empiriolabsai
Markdown alternate of the page above; the site index is https://savrn.com/llms.txt

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## Models

Model · Zero-shot classification

### [aplomb-1](https://savrn.com/models/aplomb-1)

[EmpirioLabs AI](https://savrn.com/model-publishers/empiriolabsai)

Aplomb 1 is our first model, a decision model. It reads text, JSON, images, video and audio, and answers typed questions about them with calibrated probabilities instead of generated text. Send a state of up to 1M tokens with up to 128 questions, and every answer comes back as a probability distribution with a confidence value, in one request. Aplomb 1 has 5.3 billion parameters. - Every input type in one model: text, JSON objects and arrays, images, video and audio. selection (which function to call, with distributions over its enum and boolean arguments). contain what the question needs. - Zero data retention by default on the hosted API: EmpirioLabs does not retain the content of…

Access requested at publisher other 5.3B parameters transformers

[View model](https://savrn.com/models/aplomb-1)

## Explore More

- [All model publishers](https://savrn.com/model-publishers)
- [The model directory](https://savrn.com/models)
- [The dataset directory](https://savrn.com/datasets)

## Source

- Listed from their public repositories, read 2026-10-04.
- [Hugging Face profile](https://huggingface.co/empiriolabsai)
- [How the hub is built](https://savrn.com/model-hub/methodology)