Open Source
bitsandbytes
Accessible large language models via k-bit quantization for PyTorch.
Our verdict
We have not reviewed bitsandbytes yet
No one at Enterprise DNA has checked this listing against its sources. The description comes from public listings gathered automatically. Any fact below shows where it came from and when it was last checked.
From the listing
About bitsandbytes
bitsandbytes provides k-bit quantization for PyTorch, enabling large language models to run on hardware with limited memory. It reduces model precision to 8-bit or 4-bit to lower GPU memory usage while maintaining acceptable performance.
Best for
Developers who need to run or fine-tune large language models on GPU-constrained hardware
Use cases
- Load and run 7B, 13B, or larger LLMs on consumer-grade GPUs
- Fine-tune pretrained models using 4-bit or 8-bit quantization
- Reduce memory footprint for deploying LLMs in production
Notes
8,246 stars on GitHub. Last updated 2026-06-01. Licensed MIT.
Pros
- Significantly reduces GPU memory requirements for large models
- Enables LLM inference and training on widely available hardware
- Open source with strong community adoption and regular updates
Cons
- Not all model architectures are compatible with k-bit quantization
- Lower bit widths can lead to slight degradation in model accuracy
- Requires adjusting quantization parameters for optimal results
Key facts
What we have checked
- Latest prerelease version
- continuous-release_main (released 3 Sept 2026)
- GitHub stars
- 8,499
Each value shows when we last confirmed it and where it came from. Values we have not confirmed are left out, never guessed.
Stars and usage
How bitsandbytes is growing
8,246 to 8,499
Sources
Where this comes from
- GitHubOfficial
- github api via nightly crawl, recovered from git history 20e874270887c1008f860ee0198e461a23c9e438Registry
A source shows what was published when we checked it. It does not certify security, performance or a working installation. Read our method.
Changelog
What changed
Released continuous-release_main
Released 0.50.2
Released 0.50.1
Released 0.50.0
Released 0.49.2
Released 0.49.1
Released 0.49.0
Released 0.48.2
Released 0.48.1
Released 0.48.0
Pairs with
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