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Releases: bitsandbytes-foundation/bitsandbytes

0.48.0: Intel GPU & Gaudi support, CUDA 13, performance improvements, and more!

30 Sep 21:48
@matthewdouglas matthewdouglas
0.48.0
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0.48.0: Intel GPU & Gaudi support, CUDA 13, performance improvements, and more! Latest
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Highlights

🎉 Intel GPU Support

We now officially support Intel GPUs on Linux and Windows! Support is included for all major features (LLM.int8(), QLoRA, 8bit optimizers) with the exception of the paged optimizer feature.

This support includes the following hardware:

  • Intel® Arc™ B-Series Graphics
  • Intel® Arc™ A-Series Graphics
  • Intel® Data Center GPU Max Series

A compatible PyTorch version with Intel XPU support is required. The current minimum is PyTorch 2.6.0. It is recommended to use the latest stable release. See Getting Started on Intel GPU for guidance.

🎉 Intel Gaudi Support

We now officially support Intel Gaudi2 and Gaudi3 accelerators. This support includes LLM.int8() and QLoRA with the NF4 data type. At this time optimizers are not implemented.

A compatible PyTorch version with Intel Gaudi support is required. The current minimum is Gaudi v1.21 with PyTorch 2.6.0. It is recommended to use the latest stable release. See the Gaudi software installation guide for guidance.

NVIDIA CUDA

  • The 4bit dequantization kernel was improved by @Mhmd-Hisham in #1746. This change brings noticeable speed improvements for prefill, batch token generation, and training. The improvement is particularly prominent on A100, H100, and B200.
  • We've added CUDA 13.0 compatibility across Linux x86-64, Linux aarch64, and Windows x86-64 platforms.
    • Hardware support for CUDA 13.0 is limited to Turing generation and newer.
    • Support for Thor (SM110) is available in the Linux aarch64 build.

🚨 Breaking Changes

  • Dropped support for PyTorch 2.2. The new minimum requirement is 2.3.0.
  • Removed Maxwell GPU support for all CUDA builds.

What's Changed

New Contributors

Full Changelog: 0.47.0...0.48.0

Contributors

jasl, Egor-Krivov, and 9 other contributors
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Latest `main` wheel

30 Sep 23:46
@github-actions github-actions
continuous-release_main
00c0a1a
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Latest `main` wheel Pre-release
Pre-release

Latest main pre-release wheel

This pre-release contains the latest development wheels for all supported platforms, rebuilt automatically on every commit to the main branch.

How to install:
Pick the correct command for your platform and run it in your terminal:

Linux (ARM/aarch64)

pip install --force-reinstall https://github.com/bitsandbytes-foundation/bitsandbytes/releases/download/continuous-release_main/bitsandbytes-1.33.7.preview-py3-none-manylinux_2_24_aarch64.whl

Linux (x86_64)

pip install --force-reinstall https://github.com/bitsandbytes-foundation/bitsandbytes/releases/download/continuous-release_main/bitsandbytes-1.33.7.preview-py3-none-manylinux_2_24_x86_64.whl

Windows (x86_64)

pip install --force-reinstall https://github.com/bitsandbytes-foundation/bitsandbytes/releases/download/continuous-release_main/bitsandbytes-1.33.7.preview-py3-none-win_amd64.whl

Note:
These wheels are updated automatically with every commit to main and become available as soon as the python-package.yml workflow finishes.

The version number is replaced with 1.33.7-preview in order to keep the link stable, this however does not affect the installed version at all:

> pip install https://.../bitsandbytes-1.33.7-preview-py3-none-manylinux_2_24_x86_64.whl
Collecting bitsandbytes==1.33.7rc0
...
Successfully installed bitsandbytes-0.46.0.dev0
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0.47.0

11 Aug 18:59
@matthewdouglas matthewdouglas
0.47.0
c0dcdf2
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0.47.0

Highlights:

  • FSDP2 compatibility for Params4bit (#1719)
  • Bugfix for 4bit quantization with large block sizes (#1721)
  • Further removal of previously deprecated code (#1669)
  • Improved CPU coverage (#1628)
  • Include NVIDIA Volta support in CUDA 12.8 and 12.9 builds (#1715)

What's Changed

New Contributors

Full Changelog: 0.46.0...0.47.0

Contributors

mgorny, Egor-Krivov, and 8 other contributors
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0.46.1

02 Jul 19:45
@matthewdouglas matthewdouglas
0.46.1
4bca844
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0.46.1

What's Changed

New Contributors

Full Changelog: 0.46.0...0.46.1

Contributors

mgorny, mklabunde, and 3 other contributors
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0.46.0: torch.compile() support; custom ops refactor; Linux aarch64 wheels

27 May 21:27
@matthewdouglas matthewdouglas
0.46.0
1e54f91
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0.46.0: torch.compile() support; custom ops refactor; Linux aarch64 wheels

Highlights

  • Support for torch.compile without graph breaks for LLM.int8().
    • Compatible with PyTorch 2.4+, but PyTorch 2.6+ is recommended.
    • Experimental CPU support is included.
  • Support torch.compile without graph breaks for 4bit.
    • Compatible with PyTorch 2.4+ for fullgraph=False.
    • Requires PyTorch 2.8 nightly for fullgraph=True.
  • We are now publishing wheels for CUDA Linux aarch64 (sbsa)!
    • Targets are Turing generation and newer: sm75, sm80, sm90, and sm100.
  • PyTorch Custom Operators refactoring and integration:
    • We have refactored most of the library code to integrate better with PyTorch via the torch.library and custom ops APIs. This helps enable our torch.compile and additional hardware compatibility efforts.
    • End-users do not need to change the way they are using bitsandbytes.
  • Unit tests have been cleaned up for increased determinism and most are now device-agnostic.
    • A new nightly CI runs unit tests for CPU (Windows x86-64, Linux x86-64/aarch64) and CUDA (Linux/Windows x86-64).

Compatability Changes

  • Support for Python 3.8 is dropped.
  • Support for PyTorch < 2.2.0 is dropped.
  • CUDA 12.6 and 12.8 builds are now compatible for manylinux_2_24 (previously manylinux_2_34).
  • Many APIs that were previously marked as deprecated have now been removed.
  • New deprecations:
    • bnb.autograd.get_inverse_transform_indices()
    • bnb.autograd.undo_layout()
    • bnb.functional.create_quantile_map()
    • bnb.functional.estimate_quantiles()
    • bnb.functional.get_colrow_absmax()
    • bnb.functional.get_row_absmax()
    • bnb.functional.histogram_scatter_add_2d()

What's Changed

New Contributors

Full Changelog: 0.45.4...0.46.0

Contributors

winglian, Egor-Krivov, and 7 other contributors
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Multi-Backend Preview

19 May 13:24
@github-actions github-actions
continuous-release_multi-backend-refactor
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Multi-Backend Preview Pre-release
Pre-release 
continuous-release_multi-backend-refactor

update compute_type_is_set attr (#1623)
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0.45.5

07 Apr 13:37
@matthewdouglas matthewdouglas
0.45.5
d72cb9c
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0.45.5

This is a minor release that affects CPU-only usage of bitsandbytes. The CPU build of the library was inadvertently omitted from the v0.45.4 wheels.

Full Changelog: 0.45.4...0.45.5

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0.45.4

25 Mar 16:41
@matthewdouglas matthewdouglas
0.45.4
f0735f9
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0.45.4

This is a minor release that affects CPU-only usage of bitsandbytes. There is one bugfix and improved system compatibility on Linux.

What's Changed

  • Build: use ubuntu-22.04 instead of 24.04 for CPU build (glibc compat) by @matthewdouglas in #1538
  • Fix CPU dequantization to use nested dequantized scaling constant by @zyklotomic in #1549

New Contributors

Full Changelog: 0.45.3...0.45.4

Contributors

zyklotomic and matthewdouglas
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0.45.3

24 Feb 19:50
@matthewdouglas matthewdouglas
0.45.3
efc14c1
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0.45.3

Overview

This is a small patch release containing a few bug fixes.

Additionally, this release contains a CUDA 12.8 build which adds the sm100 and sm120 targets for NVIDIA Blackwell GPUs.

What's Changed

New Contributors

Full Changelog: 0.45.2...0.45.3

Contributors

mitchellgoffpc, johnnynunez, and 2 other contributors
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0.45.2

06 Feb 19:03
@matthewdouglas matthewdouglas
0.45.2
7aec4a8
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0.45.2

This patch release fixes a compatibility issue with Triton 3.2 in PyTorch 2.6. When importing bitsandbytes without any GPUs visible in an environment with Triton installed, a RuntimeError may be raised:

RuntimeError: 0 active drivers ([]). There should only be one.

Full Changelog: 0.45.1...0.45.2

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