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darkstarinitiative/
AJAN-SIMIT-Ternary-Bonsai-Q2_0-GGUF

Name: AJAN-SIMIT-Ternary-Bonsai-Q2_0-GGUF
Availability: InStock

prism-ml/Ternary-Bonsai-1.7B-gguf

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AJAN-SIMIT Ternary-Bonsai Q2_0 (GGUF)

Q2_0 GGUF quantizations of Prism ML's Ternary-Bonsai model family, produced by DarkStar Initiative for the Ajan Simit offline mobile AI project (an on-device Android voice assistant).

We did not train or create the base model. This repository contains only our own re-quantization of Prism ML's publicly released weights, done so the model is small enough to run entirely on-device on a phone.

Provenance / credits

Base model: Qwen3-1.7B (Apache 2.0, Qwen team)
Ternary fine-tune: prism-ml/Ternary-Bonsai (Apache 2.0, Prism ML)
This Q2_0 re-quantization: DarkStar Initiative / Ajan Simit, produced with a self-built llama-quantize from Prism ML's own fork, PrismML-Eng/llama.cpp (prism branch) -- credited per their own model card's request.
License: Apache 2.0, inherited unchanged from the base model and the fine-tune. No added restrictions. A full copy of the license text is included in this repo as LICENSE.

If you use the original Ternary-Bonsai model itself (not just this re-quantization), please cite Prism ML directly:

bibtex

@techreport{ternarybonsai,
  title  = {Ternary Bonsai: 1.58-bit Language Models},
  author = {Prism ML},
}

What's different from the upstream Prism ML release

Only the quantization level and the file/repo naming:

Quantization: Q2_0 (2.125 bpw), quantized from Prism ML's F16 release. No retraining, no architecture changes, no fine-tuning of our own.
Naming: the AJAN-SIMIT- prefix marks these files as our own community re-quantization and build, produced for the Ajan Simit app specifically -- not an official Prism ML release, and not endorsed by Prism ML or the Qwen team.

Files

File	Size
`AJAN-SIMIT-Ternary-Bonsai-1.7B-Q2_0.gguf`	~463 MB
`AJAN-SIMIT-Ternary-Bonsai-4B-Q2_0.gguf`	~1.07 GB
`AJAN-SIMIT-Ternary-Bonsai-8B-Q2_0.gguf`	~2.18 GB
`AJAN-SIMIT-Ternary-Bonsai-27B-Q2_0.gguf`	~8.25 GB

Usage

Compatible with any recent llama.cpp-based inference engine. Q2_0 is a first-class quant type in Prism ML's llama.cpp fork; mainline llama.cpp support may vary by version.

darkstarinitiative/AJAN-SIMIT-Ternary-Bonsai-Q2_0-GGUF