turboquant-mlx
turboquant-mlx packages a small MLX-oriented reference implementation of the
TurboQuant building blocks described in arXiv:2504.19874:
- orthogonal rotations
- scalar codebooks
- polar quantization for keys and values
- a 1-bit QJL sketch
- outlier channel handling
Installation
python -m pip install turboquant-mlx
For development:
python -m pip install -e ".[dev]"
pytest
Runtime requirements
The package depends on mlx and therefore targets Apple Silicon macOS
environments where MLX is supported. The test suite uses a lightweight stub for
mlx.core so package logic can still be validated in environments where the
Metal runtime is unavailable.
Package contents
Rotation: fast Walsh-Hadamard or dense QR rotationsCodebook: scalar quantization codebooks and persistence helpersPolarQuant: key/value encode-decode helpersSplitTurboQuant: paper-style mixed-precision split quantization for 2.5/3.5-bit setupsQJL: 1-bit quantized Johnson-Lindenstrauss sketchOutlierHandler: EMA-based outlier channel selection for routing channels into the higher-bit split quantizer
Metadata
Release files for turboquant-mlx 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| turboquant_mlx-0.1.0.tar.gz | 11.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| turboquant_mlx-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 20.3 kB
Release files / turboquant_mlx-0.1.0.tar.gz
| Download URL | turboquant_mlx-0.1.0.tar.gz |
|---|---|
| Size | 11.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/6.2.0 CPython/3.13.12
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Release files / turboquant_mlx-0.1.0-py3-none-any.whl
| Download URL | turboquant_mlx-0.1.0-py3-none-any.whl |
|---|---|
| Size | 9.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.13.12
|