Comparison
bitsandbytes vs exllama
Verdict
Pick bitsandbytes if bitsandbytes provides k-bit quantization in PyTorch, enhancing large language model accessibility across multiple hardware platforms; pick exllama if exLlama provides a memory-efficient implementation of the LLaMa model with support for quantized weights, primarily aimed at users with NVIDIA GPUs from the 30-series onwards.
Markdown twin · bitsandbytes alternatives · exllama alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | bitsandbytes | exllama |
|---|---|---|
| Maintenance | Very active (5d since push) As of 3w · github_public_v1 | Dormant (1041d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Personal account As of 2w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | Published findings As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- bitsandbytes
- Large language model quantization toolkit for PyTorch.
- exllama
- Memory-efficient rewrite of HF transformers for Llama with quantized weights
Stars
- bitsandbytes
- 8.4k
- exllama
- 2.9k
Forks
- bitsandbytes
- 900
- exllama
- 220
Open issues
- bitsandbytes
- 54
- exllama
- 65
Language
- bitsandbytes
- Python
- exllama
- Python
Adopt for
- bitsandbytes
- bitsandbytes provides k-bit quantization in PyTorch, enhancing large language model accessibility across multiple hardware platforms.
- exllama
- ExLlama provides a memory-efficient implementation of the LLaMa model with support for quantized weights, primarily aimed at users with NVIDIA GPUs from the 30-series onwards.
Persona
- bitsandbytes
- -
- exllama
- -
Runtime
- bitsandbytes
- -
- exllama
- -
License
- bitsandbytes
- MIT
- exllama
- MIT
Last pushed
- bitsandbytes
- Jul 29, 2026
- exllama
- Sep 30, 2023
Categories
- bitsandbytes
- Inference & Serving, LLM Frameworks
- exllama
- Inference & Serving, LLM Frameworks
Trust and health
Maintenance
- bitsandbytes
- Very active (96%)
- exllama
- Dormant (18%)
Days since push
- bitsandbytes
- 5d
- exllama
- 1041d
Open issues (now)
- bitsandbytes
- 54
- exllama
- 65
Owner type
- bitsandbytes
- Organization
- exllama
- User
OSV dependency advisories
- bitsandbytes
- No lockfile (source not queried)
- exllama
- Published findings
Full report
- bitsandbytes
- Trust report
- exllama
- Trust report
Choose bitsandbytes if…
- 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.
- More GitHub stars (8.4k vs 2.9k) - visibility, not fit.
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.
Choose exllama if…
- Tags unique to exllama: docker, llama model, memory-efficient, nvidia gpu.
- exllama ships Docker support for self-hosted deployment.
- - When deploying LLaMa models on NVIDIA GPUs from the 30-series or later that have strong FP16 support.
When NOT to use exllama
- - If you are operating older GPUs such as Pascal series, which lack robust FP16 support; alternatives like AutoGPTQ might perform better.
- - In scenarios that involve AMD GPU hardware (due to limited testing and optimization efforts).
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (bitsandbytes-foundation/bitsandbytes) · observed Aug 4, 2026
- GitHub forks (bitsandbytes-foundation/bitsandbytes) · observed Aug 4, 2026
- Last push (bitsandbytes-foundation/bitsandbytes) · observed Jul 29, 2026
- License file (MIT) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (turboderp/exllama) · observed Aug 7, 2026
- GitHub forks (turboderp/exllama) · observed Aug 7, 2026
- Last push (turboderp/exllama) · observed Sep 30, 2023
- License file (MIT) · observed Aug 7, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: bitsandbytes 8.4k · exllama 2.9k (synced Aug 4, 2026).
Common questions
- What is the difference between bitsandbytes and exllama?
- bitsandbytes: Large language model quantization toolkit for PyTorch.. exllama: Memory-efficient rewrite of HF transformers for Llama with quantized weights. See the comparison table for live GitHub stats and shared categories.
- When should I choose bitsandbytes over exllama?
- Choose bitsandbytes over exllama when 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; More GitHub stars (8.4k vs 2.9k) - visibility, not fit.
- When should I choose exllama over bitsandbytes?
- Choose exllama over bitsandbytes when Tags unique to exllama: docker, llama model, memory-efficient, nvidia gpu; exllama ships Docker support for self-hosted deployment; - When deploying LLaMa models on NVIDIA GPUs from the 30-series or later that have strong FP16 support.
- 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 exllama?
- - If you are operating older GPUs such as Pascal series, which lack robust FP16 support; alternatives like AutoGPTQ might perform better. - In scenarios that involve AMD GPU hardware (due to limited testing and optimization efforts).
- Is bitsandbytes or exllama more popular on GitHub?
- bitsandbytes has more GitHub stars (8,385 vs 2,937). Stars measure visibility, not whether either tool fits your constraints.
- Are bitsandbytes and exllama open source?
- Yes - both are open-source projects on GitHub (bitsandbytes: MIT, exllama: MIT).
- Where can I find alternatives to bitsandbytes or exllama?
- GraphCanon lists graph-backed alternatives at bitsandbytes alternatives and exllama alternatives (bitsandbytes markdown twin, exllama markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, bitsandbytes or exllama?
- bitsandbytes: Very active. exllama: Dormant. 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 exllama?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: bitsandbytes trust report; exllama trust report.