Models

Open Australian models

Every model we release has open weights, a published licence and a model card that sets out what it was trained on and where it falls short.

Hugging FaceGitHub

01 / Released

Download today

01

piper-en_AU-librivox-medium

Ten Australian English voices for Piper, the open source text to speech engine. Trained on public domain LibriVox recordings, small enough to run on a CPU, and fully offline.

  • ~70M parameters
  • 77 MB
  • Runs on CPU
  • CC BY 4.0
View on Hugging Face
Text to speech

02 / In development

What we are training next

No results are claimed for these models until they are measured and published.

01 / Training now

Australis Black Opal

The first model in our Australis text family: a recurrent language model, built as a 26B mixture of experts model for long documents, code, tools and Australian workplace tasks.

  • Gemma 4
  • Recurrent depth
  • Australian English
  • Text + image
  • Open weights
  • Apache 2.0
Base model
google/gemma-4-26B-A4B-it
Architecture
Gemma mixture of experts. Recurrent depth must beat the native model at matched compute before it ships.
Precision
NVFP4 deployment build. We will publish the final mixed precision map after measurement
Built to handle
Long documents, code, tools and real Australian workplace tasks
Deployment
One 32 GB+ Blackwell class workstation GPU
Quality target
An independent evaluator must measure ≥20 on the AA Intelligence Index. Australian benchmarks cover lexis, spelling, culture and knowledge, and the model must retain general and multimodal capability.
At release
Open weights, per task results including failures, and a technical report covering data, training and trade offs

02 / Up next

Umpire

Our open Australian decision model. Inspired by TypeSafe AI's Jev, it is designed to make the call: choose from a fixed set of options, fast, with Australian context, institutions and logic.

  • Open source
  • Australian logic
  • Decision reasoning
Purpose
Make structured decisions using Australian assumptions and context rather than relying on overseas defaults
Approach
Build an openly available Australian counterpart to models such as Jev

03 / Planned

Lyrebird

Our next generation Australian voice model: higher quality, to succeed our first Piper release and move beyond its 29.6 hour training run.

  • Text to speech
  • Australian English
  • Open source
  • Piper successor
Starting point
Lessons from piper-en_AU-librivox-medium, our first voice model, trained for 29.6 hours
Goal
A next generation voice system with more voices, a larger training effort, better voice quality and potentially different base

04 / Seeking compute

Australis Olympic

The flagship of the Australis family, named for the Olympic Australis, the largest gem opal ever found. A new language model pretrained from the ground up under a new architecture. This is the long term project, and it depends on funding and access to substantial GPU compute.

  • Pretraining
  • New architecture
  • From scratch
  • Funding required
  • GPU compute required
Research direction
Design and pretrain a language model rather than adapting an existing base model
Dependency
External funding, GPU hardware or cloud compute sufficient for pretraining
Status
Work on the architecture and training programme will begin when we secure the required resources
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