@sudoingX: this lab took qwen 3.6 27b, the model i've been calling king of the 24gb tier all month, and crushed it down to 3.9gb. …

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Summary

PrismML announces Bonsai 27B, a binary-quantized version of Qwen3.6 27B that runs on a phone using only 1.125 bits per weight, claiming 89.5% intelligence retention. The model is being independently tested by @sudoingX to verify performance.

this lab took qwen 3.6 27b, the model i've been calling king of the 24gb tier all month, and crushed it down to 3.9gb. that's it on my screen right now, loaded now on my single 3090, using less memory than a gemma 12b. here's what they actually did, because it matters. no retraining, no new model. they took the existing weights and quantized them to binary, one sign bit per weight with a shared scale every 128, the whole 27b of it, embeddings, attention, all of it, packed into 1.125 bits. it should be broken. sub 4 bit is where models usually turn to mush. prismml claims it keeps 89.5% of the full model's intelligence. bold. i already own the real qwen 3.6 27b numbers from my own bench, so i'm going to make it prove that. same agent tasks, same tests, 1 bit against the honest q4, and we find exactly where it breaks. running it now. receipts coming.
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Cached at: 07/16/26, 08:23 PM

this lab took qwen 3.6 27b, the model i’ve been calling king of the 24gb tier all month, and crushed it down to 3.9gb. that’s it on my screen right now, loaded now on my single 3090, using less memory than a gemma 12b.

here’s what they actually did, because it matters. no retraining, no new model. they took the existing weights and quantized them to binary, one sign bit per weight with a shared scale every 128, the whole 27b of it, embeddings, attention, all of it, packed into 1.125 bits. it should be broken. sub 4 bit is where models usually turn to mush.

prismml claims it keeps 89.5% of the full model’s intelligence. bold. i already own the real qwen 3.6 27b numbers from my own bench, so i’m going to make it prove that. same agent tasks, same tests, 1 bit against the honest q4, and we find exactly where it breaks.

running it now. receipts coming.

PrismML (@PrismML): Today, we’re announcing Bonsai 27B: the first 27B-class model to run on a phone.

Bonsai 27B is the new multimodal flagship of the Bonsai family. Based on Qwen3.6 27B, it brings a new capability tier to local AI: multi-step reasoning, structured tool use, long-context workflows,

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Bonsai-27B is a 1-bit binary transformer model that achieves full 27B-class reasoning on a phone (iPhone 17 Pro Max) with ~3.9 GB footprint and ~11 tok/s, retaining ~90% of FP16 intelligence.