--- title: "bitsandbytes vs scaling-book" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/bitsandbytes-foundation-bitsandbytes-vs-jax-ml-scaling-book" tools: ["bitsandbytes-foundation-bitsandbytes", "jax-ml-scaling-book"] --- # bitsandbytes vs scaling-book *GraphCanon updated Aug 25, 2026* ## Verdict Pick bitsandbytes if bitsandbytes provides k-bit quantization in PyTorch, enhancing large language model accessibility across multiple hardware platforms; pick scaling-book if scaling-book. [bitsandbytes](https://huggingface.co/docs/bitsandbytes/main/en/index) reports 8.4k GitHub stars, 900 forks, and 54 open issues, last pushed Jul 29, 2026. [scaling-book](https://jax-ml.github.io/scaling-book/) has 1.4k stars, 191 forks, and 8 open issues, last pushed Aug 20, 2026. Figures are from public GitHub metadata via [bitsandbytes's repository](https://github.com/bitsandbytes-foundation/bitsandbytes) and [scaling-book's repository](https://github.com/jax-ml/scaling-book). | | [bitsandbytes](/tools/bitsandbytes-foundation-bitsandbytes.md) | [scaling-book](/tools/jax-ml-scaling-book.md) | | --- | --- | --- | | Tagline | Large language model quantization toolkit for PyTorch. | Guide on scaling LLMs on TPUs | | Stars | 8,385 | 1,368 | | Forks | 900 | 191 | | Open issues | 54 | 8 | | Language | Python | HTML | | Adopt for | bitsandbytes provides k-bit quantization in PyTorch, enhancing large language model accessibility across multiple hardware platforms. | scaling-book | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Inference & Serving, LLM Frameworks | Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [bitsandbytes](/tools/bitsandbytes-foundation-bitsandbytes.md) | [scaling-book](/tools/jax-ml-scaling-book.md) | | --- | --- | --- | | Days since push | 5d | 4d | | Open issues (now) | 54 | 8 | | Stars delta | Unknown | +77 (30d) | | Open issues delta | Unknown | +1 (30d) | | Full report | [trust report](/tools/bitsandbytes-foundation-bitsandbytes/trust.md) | [trust report](/tools/jax-ml-scaling-book/trust.md) | ## Shared compatibility - **Python**: [bitsandbytes](/tools/bitsandbytes-foundation-bitsandbytes.md) - Python runtime; [scaling-book](/tools/jax-ml-scaling-book.md) - Python runtime ## Decision facts: bitsandbytes - **Adopt for:** bitsandbytes provides k-bit quantization in PyTorch, enhancing large language model accessibility across multiple hardware platforms. ## Decision facts: scaling-book - **Adopt for:** scaling-book ## Choose when ### Choose bitsandbytes if… - bitsandbytes is primarily Python; scaling-book is HTML. - Tags unique to bitsandbytes: llm, machine-learning, pytorch, qlora. - When you need advanced k-bit quantization on PyTorch for hardware like NVIDIA GPUs with SM75+ recommended. ### Choose scaling-book if… - scaling-book is primarily HTML; bitsandbytes is Python. - Tags unique to scaling-book: jax, llm-inference, llms, roofline. - You are working specifically with machine learning models that leverage Tensor Processing Units (TPUs) for performance and are looking to understand optimization techniques. ## When NOT to use bitsandbytes - Avoid if your setup includes Intel Gaudi processors as QLoRA 4-bit support is partial and 8-bit optimizers are not available. - Steer clear if you require full compatibility with ARM-based CPUs, as specific GPU optimizations might lack coverage. ## When NOT to use scaling-book - Do not use if your project focuses exclusively on GPU scaling or other hardware not aligned with Tensor Processing Units (TPUs). - If you are looking for a general approach to any framework's scalability without emphasis on TPUs. - This resource is unsuitable if you need information about model training phases, as it emphasizes inference and serving phases. ## Common questions ### What is the difference between bitsandbytes and scaling-book? bitsandbytes: Large language model quantization toolkit for PyTorch.. scaling-book: Guide on scaling LLMs on TPUs. See the comparison table for live GitHub stats and shared categories. ### When should I choose bitsandbytes over scaling-book? Choose bitsandbytes over scaling-book when bitsandbytes is primarily Python; scaling-book is HTML; Tags unique to bitsandbytes: llm, machine-learning, pytorch, qlora; When you need advanced k-bit quantization on PyTorch for hardware like NVIDIA GPUs with SM75+ recommended. ### When should I choose scaling-book over bitsandbytes? Choose scaling-book over bitsandbytes when scaling-book is primarily HTML; bitsandbytes is Python; Tags unique to scaling-book: jax, llm-inference, llms, roofline; You are working specifically with machine learning models that leverage Tensor Processing Units (TPUs) for performance and are looking to understand optimization techniques. ### When should I avoid bitsandbytes? Avoid if your setup includes Intel Gaudi processors as QLoRA 4-bit support is partial and 8-bit optimizers are not available. Steer clear if you require full compatibility with ARM-based CPUs, as specific GPU optimizations might lack coverage. ### When should I avoid scaling-book? Do not use if your project focuses exclusively on GPU scaling or other hardware not aligned with Tensor Processing Units (TPUs). If you are looking for a general approach to any framework's scalability without emphasis on TPUs. This resource is unsuitable if you need information about model training phases, as it emphasizes inference and serving phases. ### Is bitsandbytes or scaling-book more popular on GitHub? bitsandbytes has more GitHub stars (8,385 vs 1,368). Stars measure visibility, not whether either tool fits your constraints. ### Are bitsandbytes and scaling-book open source? Yes - both are open-source projects on GitHub (bitsandbytes: MIT, scaling-book: MIT). ### Where can I find alternatives to bitsandbytes or scaling-book? GraphCanon lists graph-backed alternatives at [bitsandbytes alternatives](/tools/bitsandbytes-foundation-bitsandbytes/alternatives) and [scaling-book alternatives](/tools/jax-ml-scaling-book/alternatives) ([bitsandbytes markdown twin](/tools/bitsandbytes-foundation-bitsandbytes/alternatives.md), [scaling-book markdown twin](/tools/jax-ml-scaling-book/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/bitsandbytes-foundation-bitsandbytes-vs-jax-ml-scaling-book.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, bitsandbytes or scaling-book? bitsandbytes: Very active. scaling-book: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for bitsandbytes and scaling-book? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [bitsandbytes trust report](/tools/bitsandbytes-foundation-bitsandbytes/trust); [scaling-book trust report](/tools/jax-ml-scaling-book/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=bitsandbytes-foundation-bitsandbytes`](/api/graphcanon/graph?tool=bitsandbytes-foundation-bitsandbytes) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_