Latest `main` wheel

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

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

• Enable CPU/XPU native and ipex path by @jiqing-feng in #1628
• Fix CI regression by @matthewdouglas in #1666
• Add CPU + IPEX to nightly CI by @matthewdouglas in #1667
• Fix params4bit passing bnb quantized by @mklabunde in #1665
• Deprecation cleanup by @matthewdouglas in #1669
• CI workflow: bump torch 2.7.0 to 2.7.1 by @matthewdouglas in #1670
• Improvement for torch.compile support on Params4bit by @matthewdouglas in #1673
• Fixed a bug in test_fw_bit_quant testing on CPU by @Egor-Krivov in #1675
• doc fix signature for 8-bit optim by @ved1beta in #1660
• Apply clang-format rules by @matthewdouglas in #1678
• Add clang-format by @matthewdouglas in #1677
• HPU (Intel gaudi) support for bnb unit tests by @ckvermaAI in #1680
• CI: Setup HPU nightly tests by @matthewdouglas in #1681
• Update test_kbit_backprop unit test by @ckvermaAI in #1682
• Update README.md by @matthewdouglas in #1684
• Enable ROCm backend with custom ops integration by @pnunna93 in #1683
• Fix AdamW documentation by @agupta2304 in #1686
• Make minor improvements to optimizer.py by @agupta2304 in #1687
• Add CUDA 12.9 build by @matthewdouglas in #1689
• CI: Test with PyTorch 2.8.0 RC by @matthewdouglas in #1693
• Automatically call CMake as part of PEP 517 build by @mgorny in #1512
• fix log by @jiqing-feng in #1697
• [XPU] Add inference benchmark for XPU by @Egor-Krivov in #1696
• Add kernel registration for 8bit and 32bit optimizers by @Egor-Krivov in #1706
• Create FUNDING.yml by @matthewdouglas in #1714
• Add Volta support in cu128/cu129 builds by @matthewdouglas in #1715
• Fix Params4bit tensor subclass handling by @ved1beta in #1719
• [CUDA] Fixing quantization uint8 packing bug for NF4 and FP4 by @Mhmd-Hisham in #1721

New Contributors

• @mklabunde made their first contribution in #1665
• @agupta2304 made their first contribution in #1686
• @mgorny made their first contribution in #1512
• @Mhmd-Hisham made their first contribution in #1721

Full Changelog: 0.46.0...0.47.0

0.46.1

What's Changed

• Fix params4bit passing bnb quantized by @mklabunde in #1665
• Improvement for torch.compile support on Params4bit by @matthewdouglas in #1673
• doc fix signature for 8-bit optim by @ved1beta in #1660
• Fix AdamW documentation by @agupta2304 in #1686
• Make minor improvements to optimizer.py by @agupta2304 in #1687
• Add CUDA 12.9 build by @matthewdouglas in #1689
• Automatically call CMake as part of PEP 517 build by @mgorny in #1512

New Contributors

• @mklabunde made their first contribution in #1665
• @agupta2304 made their first contribution in #1686
• @mgorny made their first contribution in #1512

Full Changelog: 0.46.0...0.46.1

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

• PyTorch Custom Operator Integration by @matthewdouglas in #1544
• Bump CUDA 12.8.0 build to CUDA 12.8.1 by @matthewdouglas in #1575
• Drop Python 3.8 support. by @matthewdouglas in #1574
• Test cleanup by @matthewdouglas in #1576
• Fix: Return tuple in get_cuda_version_tuple by @DevKimbob in #1580
• Fix torch.compile issue for LLM.int8() with threshold=0 by @matthewdouglas in #1581
• fix for missing cpu lib by @Titus-von-Koeller in #1585
• Fix #1588 - torch compatability for <=2.4 by @matthewdouglas in #1590
• Add autoloading for backend packages by @matthewdouglas in #1593
• Specify blocksize by @cyr0930 in #1586
• fix typo getitem by @ved1beta in #1597
• fix: Improve CUDA version detection and error handling by @ved1beta in #1599
• Support LLM.int8() inference with torch.compile by @matthewdouglas in #1594
• Updates for device agnosticism by @matthewdouglas in #1601
• Stop building for CUDA toolkit < 11.8 by @matthewdouglas in #1605
• fix intel cpu/xpu installation by @jiqing-feng in #1613
• Support 4bit torch.compile fullgraph with PyTorch nightly by @matthewdouglas in #1616
• Improve torch.compile support for int8 with torch>=2.8 nightly by @matthewdouglas in #1617
• Add simple op implementations for CPU by @matthewdouglas in #1602
• Set up nightly CI for unit tests by @matthewdouglas in #1619
• point to correct latest continuous release main by @winglian in #1621
• ARM runners (faster than cross compilation qemu) by @johnnynunez in #1539
• Linux aarch64 CI updates by @matthewdouglas in #1622
• Moved int8_mm_dequant from CPU to default backend by @Egor-Krivov in #1626
• Refresh content for README.md by @matthewdouglas in #1620
• C lib loading: add fallback with sensible error msg by @Titus-von-Koeller in #1615
• Switch CUDA builds to use Rocky Linux 8 container by @matthewdouglas in #1638
• Improvements to test suite by @matthewdouglas in #1636
• Additional CI runners by @matthewdouglas in #1639
• CI runner updates by @matthewdouglas in #1643
• Optimizer backwards compatibility fix by @matthewdouglas in #1647
• General cleanup & test improvements by @matthewdouglas in #1646
• Add torch.compile tests by @matthewdouglas in #1648
• Documentation Cleanup by @matthewdouglas in #1644
• simplified non_sign_bits by @ved1beta in #1649

New Contributors

• @DevKimbob made their first contribution in #1580
• @cyr0930 made their first contribution in #1586
• @ved1beta made their first contribution in #1597
• @winglian made their first contribution in #1621
• @Egor-Krivov made their first contribution in #1626

Full Changelog: 0.45.4...0.46.0

Multi-Backend Preview

continuous-release_multi-backend-refactor

update compute_type_is_set attr (#1623)

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

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

• @zyklotomic made their first contribution in #1549

Full Changelog: 0.45.3...0.45.4

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

• Fix #1490 by @matthewdouglas in #1496
• Blackwell binaries! by @johnnynunez in #1491
• Bug fix: Update create_dynamic_map to always return a float32 tensor by @mitchellgoffpc in #1521
• Update cuda versions in error messages by @FxMorin in #1520
• QuantState.to(): move code tensor with others to correct device by @matthewdouglas in #1528
• Installation doc updates by @matthewdouglas in #1529

New Contributors

• @mitchellgoffpc made their first contribution in #1521
• @FxMorin made their first contribution in #1520

Full Changelog: 0.45.2...0.45.3

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

0.45.1

Overview

This is a patch release containing compatibility fixes.

Highlights

• Compatibility for triton>=3.2.0
• Moved package configuration to pyproject.toml
• Build system: initial support for NVIDIA Blackwell B100 GPUs, RTX 50 Blackwell series GPUs and Jetson Thor Blackwell.
  • Note: Binaries built for these platforms are not included in this release. They will be included in future releases upon the availability of the upcoming CUDA Toolkit 12.7 and 12.8.
• Packaging: wheels will no longer include unit tests. (#1478)
• Sets the minimum PyTorch version to 2.0.0.

What's Changed

• Add installation doc for bnb on Ascend NPU by @ji-huazhong in #1442
• (chore) Remove unused dotfiles by @matthewdouglas in #1445
• Remove triton.ops, copy necessary bits here by @bertmaher in #1413
• chore: migrate config files to pyproject.toml by @SauravMaheshkar in #1373
• cleanup: remove unused kernels/C++ code by @matthewdouglas in #1458
• (Deps) Require torch 2.x and minor updates by @matthewdouglas in #1459
• FSDP-QLoRA doc updates for TRL integration by @blbadger in #1471
• Initial support blackwell by @johnnynunez in #1481
• (build) include Ada/Hopper targets in cu118 build by @matthewdouglas in #1487
• Exclude tests from distribution by @akx in #1486

New Contributors

• @bertmaher made their first contribution in #1413
• @SauravMaheshkar made their first contribution in #1373
• @blbadger made their first contribution in #1471
• @johnnynunez made their first contribution in #1481

Full Changelog: 0.45.0...0.45.1