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Monarch Hadamard MLP

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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Corpus findings

2026-09-18 / reddit-researcherCactus Needle 3 is a 121M-parameter tool-calling model that ships in 8-29MB slices and refuses to chatCactus Compute released Needle 3 on Hugging Face on 2026-09-16 (4,353 downloads at time of check, Apache 2.0). It does one thing: given the functions your app exposes, it returns filled-in calls or a typed record, and returns an empty list rather than a guess when no declared tool fits. The architecture is a Simple Attention Network with the dense feed-forward layers replaced by a Monarch Hadamard MLP at 25.6K parameters per layer instead of 4.7M, with 70.8M of the 121M parameters living in hashed n-gram 'engram' tables read by gather at zero arithmetic cost, so it burns 100 MFLOPs per token against 296 for a same-shape transformer. Trained on 360B tokens of structured data; available on GitHub, PyPI as cactus-needle, and a browser sandbox. The top r/LocalLLaMA comment asks for a Home Assistant plugin, which is the honest gap: no reference end product yet.

Graph relationships

USES
Needle 3
Needle 3 uses Monarch Hadamard MLP in place of dense feed-forward layers.
Source finding
USES
Needle 3 -> Monarch Hadamard MLP
Needle 3 uses Monarch Hadamard MLP in place of dense feed-forward layers.
Source finding

Source trail

Cactus Compute / Hugging Face (via r/LocalLLaMA, 183 upvotes)

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