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Cataloged from litert-community/Ternary-Bonsai-1.7B
All models by litert-community βTernary (INT2) .litertlm bundles of
prism-ml/Ternary-Bonsai-1.7B-unpacked,
packaged for the LiteRT-LM runtime and
Google AI Edge Gallery.
These run on the mobile GPU accelerator, not the NPU.
Recommended:
bonsai-1.7b-int2pc-4k-gpu.litertlm. The plain, unmodified build with no optimizations applied. Everything else in this repo is experimental β longer context or lighter activations, but whether a given one loads depends on your app's LiteRT / LiteRT-LM version and dependencies. Start with the recommended build; reach for an experimental one only if you specifically need what it offers.
32768 is the model's full context β max_position_embeddings for Ternary-Bonsai-1.7B is 32768,
so the long-context builds here sit at the ceiling rather than truncating it.
All bundles carry Bonsai's own chat template (Qwen3 ChatML with the reasoning block intact).
The GPU accelerator runs a float graph β INT2 is a storage format, and compute happens in fp16/fp32. Two consequences shape this list:
fp16 bundles are the most
likely to meet a runtime that won't take them.Support ranges by app, so the full set is published rather than a single "best" build.
Every bundle ships these in its LlmMetadata, so a LiteRT-LM host picks them up without
any configuration:
These are the values the bundles were built with. Override them in your host if you want different behaviour.
Any LiteRT-LM host β the AI Edge Gallery app, or litert_lm_main β with the GPU backend selected.
prism-ml/Ternary-Bonsai-1.7B-unpacked, Apache-2.0Created using Bonsai by Prism ML.
Training data: None was used here. These are post-training quantizations and repackagings of the released Bonsai checkpoint; no additional training, fine-tuning, or calibration data was involved. For the base model's training data, see the upstream Prism ML and Qwen3 model cards.
PII: No dataset was collected, processed, or shipped as part of this conversion, so no personally identifiable information is present in these artifacts beyond whatever the upstream released weights already encode.