--- title: "quals-2023 vs alpaca-lora" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/nautilus-institute-quals-2023-vs-tloen-alpaca-lora" tools: ["nautilus-institute-quals-2023", "tloen-alpaca-lora"] --- # quals-2023 vs alpaca-lora *GraphCanon updated Jul 11, 2026* ## Verdict Pick quals-2023 when quals-2023 is primarily C; alpaca-lora is Jupyter Notebook; pick alpaca-lora when alpaca-lora is primarily Jupyter Notebook; quals-2023 is C. [quals-2023](https://github.com/Nautilus-Institute/quals-2023) reports 127 GitHub stars, 11 forks, and 0 open issues, last pushed Jun 9, 2023. [alpaca-lora](https://github.com/tloen/alpaca-lora) has 19k stars, 2.2k forks, and 366 open issues, last pushed Jul 29, 2024. Figures are from public GitHub metadata via [quals-2023's repository](https://github.com/Nautilus-Institute/quals-2023) and [alpaca-lora's repository](https://github.com/tloen/alpaca-lora). | | [quals-2023](/tools/nautilus-institute-quals-2023.md) | [alpaca-lora](/tools/tloen-alpaca-lora.md) | | --- | --- | --- | | Tagline | Source code for the DEF CON 31 CTF Qualifiers. | Instruct-tune LLaMA on consumer hardware | | Stars | 127 | 18,913 | | Forks | 11 | 2,185 | | Open issues | 0 | 366 | | Language | C | Jupyter Notebook | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | - | Apache-2.0 | | Categories | Computer Vision | Model Training, Computer Vision, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [quals-2023](/tools/nautilus-institute-quals-2023.md) | [alpaca-lora](/tools/tloen-alpaca-lora.md) | | --- | --- | --- | | Days since push | 1128d | 712d | | Open issues (now) | 0 | 366 | | Owner type | Organization | User | | Security scan | No lockfile | 1 critical, 5 high, 12 medium, 28 low (1 critical, 5 high, 12 medium, 28 low) | | Full report | [trust report](/tools/nautilus-institute-quals-2023/trust.md) | [trust report](/tools/tloen-alpaca-lora/trust.md) | ## Choose when ### Choose quals-2023 if… - quals-2023 is primarily C; alpaca-lora is Jupyter Notebook. - Tags unique to quals-2023: c++. - Leaner open-issue backlog (0). ### Choose alpaca-lora if… - alpaca-lora is primarily Jupyter Notebook; quals-2023 is C. - Tags unique to alpaca-lora: jupyter notebook. - Also covers Model Training, Inference & Serving. - alpaca-lora ships Docker support for self-hosted deployment. ## When NOT to use quals-2023 - Last GitHub push was 1129 days ago (dormant maintenance, Jun 9, 2023). Validate activity before betting a new project on quals-2023. ## When NOT to use alpaca-lora - Last GitHub push was 712 days ago (dormant maintenance, Jul 29, 2024). Validate activity before betting a new project on alpaca-lora. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ## Common questions ### What is the difference between quals-2023 and alpaca-lora? quals-2023: Source code for the DEF CON 31 CTF Qualifiers.. alpaca-lora: Instruct-tune LLaMA on consumer hardware. See the comparison table for live GitHub stats and shared categories. ### When should I choose quals-2023 over alpaca-lora? Choose quals-2023 over alpaca-lora when quals-2023 is primarily C; alpaca-lora is Jupyter Notebook; Tags unique to quals-2023: c++; Leaner open-issue backlog (0). ### When should I choose alpaca-lora over quals-2023? Choose alpaca-lora over quals-2023 when alpaca-lora is primarily Jupyter Notebook; quals-2023 is C; Tags unique to alpaca-lora: jupyter notebook; Also covers Model Training, Inference & Serving; alpaca-lora ships Docker support for self-hosted deployment. ### When should I avoid quals-2023? Last GitHub push was 1129 days ago (dormant maintenance, Jun 9, 2023). Validate activity before betting a new project on quals-2023. ### When should I avoid alpaca-lora? Last GitHub push was 712 days ago (dormant maintenance, Jul 29, 2024). Validate activity before betting a new project on alpaca-lora. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ### Is quals-2023 or alpaca-lora more popular on GitHub? alpaca-lora has more GitHub stars (18,913 vs 127). Stars measure visibility, not whether either tool fits your constraints. ### Are quals-2023 and alpaca-lora open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to quals-2023 or alpaca-lora? GraphCanon lists graph-backed alternatives at [quals-2023 alternatives](/tools/nautilus-institute-quals-2023/alternatives) and [alpaca-lora alternatives](/tools/tloen-alpaca-lora/alternatives) ([quals-2023 markdown twin](/tools/nautilus-institute-quals-2023/alternatives.md), [alpaca-lora markdown twin](/tools/tloen-alpaca-lora/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/nautilus-institute-quals-2023-vs-tloen-alpaca-lora.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, quals-2023 or alpaca-lora? quals-2023: Dormant. alpaca-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 quals-2023 and alpaca-lora? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [quals-2023 trust report](/tools/nautilus-institute-quals-2023/trust); [alpaca-lora trust report](/tools/tloen-alpaca-lora/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=nautilus-institute-quals-2023`](/api/graphcanon/graph?tool=nautilus-institute-quals-2023) - 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/_