Comparison
LlamaFactory vs Open-Prompt-Injection
Verdict
Pick LlamaFactory when license: LlamaFactory is Apache-2.0, Open-Prompt-Injection is MIT; pick Open-Prompt-Injection when license: Open-Prompt-Injection is MIT, LlamaFactory is Apache-2.0.
Markdown twin · LlamaFactory alternatives · Open-Prompt-Injection alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | LlamaFactory | Open-Prompt-Injection |
|---|---|---|
| Maintenance | Very active (0d since push) As of today · github_public_v1 | Slowing (255d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Personal account As of today · github_public_v1 | Not a fork · Personal account As of today · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | No lockfile As of today · none |
Tagline
- LlamaFactory
- Unified Efficient Fine-Tuning of 100+ LLMs & VLMs
- Open-Prompt-Injection
- This repository provides a benchmark for prompt injection attacks and defenses in LLMs
Stars
- LlamaFactory
- 73k
- Open-Prompt-Injection
- 464
Forks
- LlamaFactory
- 8.9k
- Open-Prompt-Injection
- 74
Open issues
- LlamaFactory
- 1.1k
- Open-Prompt-Injection
- 14
Language
- LlamaFactory
- Python
- Open-Prompt-Injection
- Python
Adopt for
- LlamaFactory
- LlamaFactory is a sophisticated tool for fine-tuning numerous large language models and visual language models efficiently using various methods such as LoRA, QLoRA, RLHF, and quantization.
- Open-Prompt-Injection
- -
Persona
- LlamaFactory
- -
- Open-Prompt-Injection
- -
Runtime
- LlamaFactory
- -
- Open-Prompt-Injection
- -
License
- LlamaFactory
- Apache-2.0
- Open-Prompt-Injection
- MIT
Last pushed
- LlamaFactory
- Jul 10, 2026
- Open-Prompt-Injection
- Oct 29, 2025
Categories
- LlamaFactory
- Model Training, LLM Frameworks
- Open-Prompt-Injection
- AI Agents, LLM Frameworks, Model Training
Trust and health
Maintenance
- LlamaFactory
- Very active (96%)
- Open-Prompt-Injection
- Slowing (36%)
Days since push
- LlamaFactory
- 0d
- Open-Prompt-Injection
- 255d
Open issues (now)
- LlamaFactory
- 1.1k
- Open-Prompt-Injection
- 14
Full report
- LlamaFactory
- Trust report
- Open-Prompt-Injection
- Trust report
Choose LlamaFactory if…
- License: LlamaFactory is Apache-2.0, Open-Prompt-Injection is MIT.
- Tags unique to LlamaFactory: gemma, fine-tuning, deepseek, ai.
- When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA.
When NOT to use LlamaFactory
- When you are looking to fine-tune less popular or niche models that are not supported within the 100+ models covered by LlamaFactory.
- If your project specifically requires custom fine-tuning methods not available in this repository, such as certain versions of PEFT (Parameter Efficient Fine-Tuning) techniques excluding LoRA and QLoa
Choose Open-Prompt-Injection if…
- License: Open-Prompt-Injection is MIT, LlamaFactory is Apache-2.0.
- Tags unique to Open-Prompt-Injection: llms, prompt-injection, llm, python.
- Also covers AI Agents.
When NOT to use Open-Prompt-Injection
- Last GitHub push was 255 days ago (slowing maintenance, Oct 29, 2025). Validate activity before betting a new project on Open-Prompt-Injection.
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (hiyouga/LlamaFactory) · observed Jul 11, 2026
- GitHub forks (hiyouga/LlamaFactory) · observed Jul 11, 2026
- Last push (hiyouga/LlamaFactory) · observed Jul 10, 2026
- License file (Apache-2.0) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (liu00222/Open-Prompt-Injection) · observed Jul 11, 2026
- GitHub forks (liu00222/Open-Prompt-Injection) · observed Jul 11, 2026
- Last push (liu00222/Open-Prompt-Injection) · observed Oct 29, 2025
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: LlamaFactory 73k · Open-Prompt-Injection 464 (synced Jul 11, 2026).
Common questions
- What is the difference between LlamaFactory and Open-Prompt-Injection?
- LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. Open-Prompt-Injection: This repository provides a benchmark for prompt injection attacks and defenses in LLMs. See the comparison table for live GitHub stats and shared categories.
- When should I choose LlamaFactory over Open-Prompt-Injection?
- Choose LlamaFactory over Open-Prompt-Injection when License: LlamaFactory is Apache-2.0, Open-Prompt-Injection is MIT; Tags unique to LlamaFactory: gemma, fine-tuning, deepseek, ai; When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA.
- When should I choose Open-Prompt-Injection over LlamaFactory?
- Choose Open-Prompt-Injection over LlamaFactory when License: Open-Prompt-Injection is MIT, LlamaFactory is Apache-2.0; Tags unique to Open-Prompt-Injection: llms, prompt-injection, llm, python; Also covers AI Agents.
- When should I avoid LlamaFactory?
- When you are looking to fine-tune less popular or niche models that are not supported within the 100+ models covered by LlamaFactory. If your project specifically requires custom fine-tuning methods not available in this repository, such as certain versions of PEFT (Parameter Efficient Fine-Tuning) techniques excluding LoRA and QLoa
- When should I avoid Open-Prompt-Injection?
- Last GitHub push was 255 days ago (slowing maintenance, Oct 29, 2025). Validate activity before betting a new project on Open-Prompt-Injection. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- Is LlamaFactory or Open-Prompt-Injection more popular on GitHub?
- LlamaFactory has more GitHub stars (73,157 vs 464). Stars measure visibility, not whether either tool fits your constraints.
- Are LlamaFactory and Open-Prompt-Injection open source?
- Yes - both are open-source projects on GitHub (LlamaFactory: Apache-2.0, Open-Prompt-Injection: MIT).
- Where can I find alternatives to LlamaFactory or Open-Prompt-Injection?
- GraphCanon lists graph-backed alternatives at LlamaFactory alternatives and Open-Prompt-Injection alternatives (LlamaFactory markdown twin, Open-Prompt-Injection 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, LlamaFactory or Open-Prompt-Injection?
- LlamaFactory: Very active. Open-Prompt-Injection: Slowing. 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 LlamaFactory and Open-Prompt-Injection?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LlamaFactory trust report; Open-Prompt-Injection trust report.