The original BitNet paper (https://arxiv.org/pdf/2310.11453)

  BitNet: Scaling 1-bit Transformers for Large Language Models

was actually binary (weights of -1 or 1),

but then in the follow-up paper they started using 1.58bit weights (https://arxiv.org/pdf/2402.17764)

  The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

This seems to be first source of the confounding of "1-bit LLM" and ternary weights that I could find.

  In this work, we introduce a 1-bit LLM variant, namely BitNet b1.58, in which every single parameter (or weight) of the LLM is ternary {-1, 0, 1}.

Should be 1-trit.

Because lookup tables are not necessarily faster compared to 8-bit SIMD operations, at least when implemented naïvely.

Lookup tables can be fast, but it's not simpler, see T-MAC https://arxiv.org/abs/2407.00088 (Note that all comparisons with `llama.cpp` were made before I introduced the types from https://github.com/ggml-org/llama.cpp/pull/8151 where the 1.6-bit type uses the techniques described in the aforementioned blog post).

I wanted to try without lookup tables to at least have a baseline, and also because the fixed point packing idea lent itself naturally to using multiplications by powers of 3 when unpacking.