# H2O.ai: Open-Weight Models and Datasets
Source: https://savrn.com/model-publishers/h2oai
Markdown alternate of the page above; the site index is https://savrn.com/llms.txt

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## Models

Model · Image and text to text

### [h2o-lightning-4b](https://savrn.com/models/h2o-lightning-4b)

[H2O.ai](https://savrn.com/model-publishers/h2oai)

H2O-Lightning-4B is a 4B-parameter decision model from H2O.ai, built on Qwen/Qwen3.5-4B. It answers typed decision questions about a record (a document, a ticket, a policy, a conversation) and, from v1.2, about images that come with the record (photos, screenshots, scanned documents, charts). It returns a probability for every option: - yes/no (noul): gives the probability that a statement is true; It runs on unmodified vLLM 0.30.0 with a small standard-library shim in front (h2olightningshim.py). Each decision is one forward pass and one output token, so the cost is input tokens only. On JevBench v1.6.1, H2O-Lightning-4B v1.1 is #1 on the official Composite Score of open-weight systems…

Open weights apache-2.0 4.5B parameters 262,144 tokens transformers

[View model](https://savrn.com/models/h2o-lightning-4b)

## 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 2026-10-08.
- [Hugging Face profile](https://huggingface.co/h2oai)
- [How the hub is built](https://savrn.com/model-hub/methodology)