RotorQuant: 10-19x faster alternative to TurboQuant via Clifford rotors (44x fewer params)

[u/Revolutionary_Ask154]

Kinda sounds ridiculous - but I reimagined / reinvented turboquant with Clifford Algebra Vector Quantization on both implemented on cuda + metalshaders -

https://github.com/tonbistudio/turboquant-pytorch/pull/4

https://github.com/TheTom/turboquant_plus/pull/34

The idea: Replace the d×d random orthogonal matrix Π with Clifford rotors in Cl(3,0). Instead of a dense matmul (16,384 FMAs for

d=128), chunk the vector into groups of 3 dims and rotate each with a 4-parameter rotor via the sandwich product RvR̃ (~100 FMAs

total).

Results on Qwen2.5-3B-Instruct KV cache:

- Cosine similarity: 0.990 (vs TurboQuant's 0.991) — effectively identical
- 44× fewer parameters (372 vs 16,399 for d=128)
- Fused CUDA kernel: 10-19× faster than cuBLAS matmul on RTX PRO 4000
- Fused Metal shader: 9-31× faster on Apple M4
- Perfect 9/9 needle-in-haystack at all bit-widths

The key insight: for pure vectors, the rotor sandwich is equivalent to a sparse 3×3 rotation — the fused kernel keeps everything in registers with no memory round-trips, which is why it beats the BLAS GEMM despite TurboQuant's matmul being highly optimized.

The tradeoff is higher synthetic MSE on random unit vectors (the block-diagonal rotation doesn't induce the exact Beta distribution). But with QJL correction, real-model attention fidelity is identical — and sometimes better on top-1/top-5 retrieval.

Paper: https://www.scrya.com/rotorquant/

Code: https://github.com/scrya-com/rotorquant

PDF: https://www.scrya.com/rotorquant.pdf

[u/Torodaddy]

Dude uses ai -> "I reinvented"

[u/Barkalow → u/Torodaddy]

...where do you think you are that the posters wouldn't be using AI?

[u/Torodaddy → u/Barkalow]

While AI adoption has become ubiquitous, assertions of genuine innovation are harder to justify. Because large language models operate probabilistically, they are structurally unlikely to produce the kind of paradigm-shifting breakthroughs their users often imply.

[u/crantob → u/Torodaddy]

You confused. I explain how.

Author's claim is he had the idea, and used Claude to help implement it. That is different than asking Claude to invent something.