Comparison
qlora vs lora
Verdict
Pick qlora if qLoRA specializes in accelerating the fine-tuning process of quantized large language models like those in the Guanaco family; pick lora if lora is designed for quick model customization through low-rank adaptation of pre-existing diffusion models like Stable Diffusion using Jupyter Notebooks in an interactive learning environment.
Markdown twin · qlora alternatives · lora alternatives
GraphCanon updated Sep 26, 2026
10views this month
Trust & integrity
| Signal | qlora | lora |
|---|---|---|
| Maintenance | Dormant (837d since push) As of Sep 26, 2026 · github_public_v1 | Dormant (911d since push) As of Sep 19, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 26, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 19, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · 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
- qlora
- QLoRA finetuning of quantized LLMs
- lora
- Jupyter Notebook repository for fine-tuning diffusion models using Low-Rank Adaptation.
Stars
- qlora
- 11k
- lora
- 7.6k
Forks
- qlora
- 876
- lora
- 497
Open issues
- qlora
- 207
- lora
- 88
Language
- qlora
- Jupyter Notebook
- lora
- Jupyter Notebook
Adopt for
- qlora
- QLoRA specializes in accelerating the fine-tuning process of quantized large language models like those in the Guanaco family.
- lora
- Lora is designed for quick model customization through low-rank adaptation of pre-existing diffusion models like Stable Diffusion using Jupyter Notebooks in an interactive learning environment.
Persona
- qlora
- -
- lora
- -
Runtime
- qlora
- -
- lora
- -
License
- qlora
- MIT License; open-source tool for QLoRA fine-tuning process; LLaMA base models must be obtained legally as per their license terms
- lora
- The project is open-source under the Apache-2.0 license, allowing for broad use and modification with attribution.
Last pushed
- qlora
- Jun 10, 2024
- lora
- Mar 22, 2024
Categories
- qlora
- LLM Frameworks, Model Training
- lora
- Model Training
Trust and health
Days since push
- qlora
- 837d
- lora
- 911d
Open issues (now)
- qlora
- 207
- lora
- 88
Stars delta
- qlora
- +42 (30d)
- lora
- +11 (30d)
Open issues delta
- qlora
- +1 (30d)
- lora
- 0 (30d)
OSV dependency advisories
- qlora
- Published findings
- lora
- No lockfile (source not queried)
Full report
- qlora
- Trust report
- lora
- Trust report
Shared compatibility
- Python · qlora: Python runtime · lora: Python runtime
Choose qlora if…
- License: qlora is MIT, lora is Apache-2.0.
- Pricing: Open source under MIT License; requires access to LLaMA base models.
- Requirements: Installation involves installing PyTorch and specific packages from source; Works with model sizes ranging from 7B to 65B, includes recommendations for tuning different sizes.
- Tags unique to qlora: guanaco, llama models, quantization.
- Also covers LLM Frameworks.
- Need efficient fine-tuning for quantized LLaMA-based models
When NOT to use qlora
- Require native full-precision model tuning without efficiency constraints
- Focusing on non-LLaMA-based language models where specific adaptations may not apply
Choose lora if…
- License: lora is Apache-2.0, qlora is MIT.
- Requirements: Suitable for developers and researchers looking to experiment with diffusion models in an interactive Jupyter Notebook environment..
- Tags unique to lora: diffusion, lora, stable-diffusion.
- Use Lora when you need to fine-tune existing diffusion models quickly with interactive experimentation capabilities available via Jupyter Notebooks.
When NOT to use lora
- Do not use Lora when you require a more thorough or comprehensive fine-tuning approach that goes beyond quick customization through low-rank adaptation.
- Avoid Lora if your development workflow is not compatible with Jupyter Notebooks, as this is the primary environment provided by the repository.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (artidoro/qlora) · observed Sep 26, 2026
- GitHub forks (artidoro/qlora) · observed Sep 26, 2026
- Last push (artidoro/qlora) · observed Jun 10, 2024
- License file (MIT) · observed Sep 26, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (cloneofsimo/lora) · observed Sep 20, 2026
- GitHub forks (cloneofsimo/lora) · observed Sep 20, 2026
- Last push (cloneofsimo/lora) · observed Mar 22, 2024
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: qlora 11k · lora 7.6k (synced Sep 26, 2026).
Common questions
- What is the difference between qlora and lora?
- qlora: QLoRA finetuning of quantized LLMs. lora: Jupyter Notebook repository for fine-tuning diffusion models using Low-Rank Adaptation.. See the comparison table for live GitHub stats and shared categories.
- When should I choose qlora over lora?
- Choose qlora over lora when License: qlora is MIT, lora is Apache-2.0; Pricing: Open source under MIT License; requires access to LLaMA base models; Requirements: Installation involves installing PyTorch and specific packages from source; Works with model sizes ranging from 7B to 65B, includes recommendations for tuning different sizes; Tags unique to qlora: guanaco, llama models, quantization; Also covers LLM Frameworks; Need efficient fine-tuning for quantized LLaMA-based models.
- When should I choose lora over qlora?
- Choose lora over qlora when License: lora is Apache-2.0, qlora is MIT; Requirements: Suitable for developers and researchers looking to experiment with diffusion models in an interactive Jupyter Notebook environment.; Tags unique to lora: diffusion, lora, stable-diffusion; Use Lora when you need to fine-tune existing diffusion models quickly with interactive experimentation capabilities available via Jupyter Notebooks.
- When should I avoid qlora?
- Require native full-precision model tuning without efficiency constraints Focusing on non-LLaMA-based language models where specific adaptations may not apply
- When should I avoid lora?
- Do not use Lora when you require a more thorough or comprehensive fine-tuning approach that goes beyond quick customization through low-rank adaptation. Avoid Lora if your development workflow is not compatible with Jupyter Notebooks, as this is the primary environment provided by the repository.
- Is qlora or lora more popular on GitHub?
- qlora has more GitHub stars (11,021 vs 7,556). Stars measure visibility, not whether either tool fits your constraints.
- Are qlora and lora open source?
- Yes - both are open-source projects on GitHub (qlora: MIT, lora: Apache-2.0).
- Where can I find alternatives to qlora or lora?
- GraphCanon lists graph-backed alternatives at qlora alternatives and lora alternatives (qlora markdown twin, lora 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, qlora or lora?
- qlora: Dormant. lora: 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 qlora and lora?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: qlora trust report; lora trust report.