Harrison.rad.1
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- Harrison.ai
- Organisation type
- Industry
- Country
- Australia
- Published
- 5 September 2024
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Vision, Medicine, Language, Multimodal
- Task
- Visual question answering, Medical diagnosis
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Training data
- tokens
Availability
Whether you can obtain the model and run it on your own hardware, which is what decides if any of the graphics-card figures on this page apply.
- Weights
- Closed — provider access only
- Model access
- Unreleased
- Training code
- Unreleased
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Why it is tracked
- SOTA improvement
- Record confidence
- Unknown
It surpasses other foundational models on the challenging Fellowship of the Royal College of Radiologists (FRCR) 2B Rapids examination – an exam that only 40-59% of human radiologists manage to pass on their first attempt. When reattempted within a year of passing, radiologists score an average of 50.88 out of 601. Harrison.rad.1 performed on par with accredited and experienced radiologists at 51.4 out of 60, while other competing models such as OpenAI’s GPT-4o, Anthropic’s Claude-3.5-sonnet, Go…
Sources
Where this record came from and when it was last checked.
- Reference
- Harrison.ai launches world-leading AI model to transform healthcare
- Last updated
- 28 November 2025
What the numbers mean
About this model
Harrison.rad.1 was published by Harrison.ai, in Australia, in September 2024. industry is the category the publisher falls under.
It works in Vision, Medicine, Language, Multimodal, and is recorded as doing visual question answering, Medical diagnosis.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
Training and provenance
Its inclusion criterion is sOTA improvement.
Answers
Harrison.rad.1 — common questions
What GPU do I need to run Harrison.rad.1?
None. Harrison.rad.1 is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
Is Harrison.rad.1 open source?
No. Harrison.rad.1 has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does Harrison.rad.1 have?
No parameter count has been published for Harrison.rad.1, which is why no memory or speed figure appears on this page.
Who created Harrison.rad.1?
Harrison.rad.1 was published by Harrison.ai, based in Australia, categorised as industry.
When was Harrison.rad.1 released?
Harrison.rad.1 was published in September 2024. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
What is Harrison.rad.1 used for?
Harrison.rad.1 works in Vision, Medicine, Language, Multimodal, and is recorded as handling visual question answering, Medical diagnosis. These are the areas it was designed around; they describe intent rather than a hard boundary.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.