---
title: "circuit-breakers vs LlamaFactory"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/grayswanai-circuit-breakers-vs-hiyouga-llamafactory"
tools: ["grayswanai-circuit-breakers", "hiyouga-llamafactory"]
---

# circuit-breakers vs LlamaFactory

*GraphCanon updated Jul 11, 2026*

## Verdict

Pick circuit-breakers when circuit-breakers is primarily Jupyter Notebook; LlamaFactory is Python; pick LlamaFactory when llamaFactory is primarily Python; circuit-breakers is Jupyter Notebook.

[circuit-breakers](https://github.com/GraySwanAI/circuit-breakers) reports 265 GitHub stars, 43 forks, and 13 open issues, last pushed Sep 24, 2024. [LlamaFactory](https://llamafactory.readthedocs.io) has 73k stars, 8.9k forks, and 1.1k open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [circuit-breakers's repository](https://github.com/GraySwanAI/circuit-breakers) and [LlamaFactory's repository](https://github.com/hiyouga/LlamaFactory).

| | [circuit-breakers](/tools/grayswanai-circuit-breakers.md) | [LlamaFactory](/tools/hiyouga-llamafactory.md) |
| --- | --- | --- |
| Tagline | Improving Alignment and Robustness with Circuit Breakers | Unified Efficient Fine-Tuning of 100+ LLMs & VLMs |
| Stars | 265 | 73,157 |
| Forks | 43 | 8,937 |
| Open issues | 13 | 1,067 |
| Language | Jupyter Notebook | Python |
| Adopt for | - | 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. |
| Persona | - | - |
| Runtime | - | - |
| License | MIT | Apache-2.0 |
| Categories | LLM Frameworks, Model Training | LLM Frameworks, Model Training |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [circuit-breakers](/tools/grayswanai-circuit-breakers.md) | [LlamaFactory](/tools/hiyouga-llamafactory.md) |
| --- | --- | --- |
| Maintenance | Dormant (18%) | Very active (96%) |
| Days since push | 655d | 0d |
| Open issues (now) | 13 | 1.1k |
| Owner type | Organization | User |
| Full report | [trust report](/tools/grayswanai-circuit-breakers/trust.md) | [trust report](/tools/hiyouga-llamafactory/trust.md) |

## Decision facts: LlamaFactory

- **Adopt for:** 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.

## Choose when

### Choose circuit-breakers if…

- circuit-breakers is primarily Jupyter Notebook; LlamaFactory is Python.
- License: circuit-breakers is MIT, LlamaFactory is Apache-2.0.
- Tags unique to circuit-breakers: jupyter notebook.

### Choose LlamaFactory if…

- LlamaFactory is primarily Python; circuit-breakers is Jupyter Notebook.
- License: LlamaFactory is Apache-2.0, circuit-breakers 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 circuit-breakers

- Last GitHub push was 655 days ago (dormant maintenance, Sep 24, 2024). Validate activity before betting a new project on circuit-breakers.
- 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.

## 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

## Common questions

### What is the difference between circuit-breakers and LlamaFactory?

circuit-breakers: Improving Alignment and Robustness with Circuit Breakers. LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. See the comparison table for live GitHub stats and shared categories.

### When should I choose circuit-breakers over LlamaFactory?

Choose circuit-breakers over LlamaFactory when circuit-breakers is primarily Jupyter Notebook; LlamaFactory is Python; License: circuit-breakers is MIT, LlamaFactory is Apache-2.0; Tags unique to circuit-breakers: jupyter notebook.

### When should I choose LlamaFactory over circuit-breakers?

Choose LlamaFactory over circuit-breakers when LlamaFactory is primarily Python; circuit-breakers is Jupyter Notebook; License: LlamaFactory is Apache-2.0, circuit-breakers 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 avoid circuit-breakers?

Last GitHub push was 655 days ago (dormant maintenance, Sep 24, 2024). Validate activity before betting a new project on circuit-breakers. 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.

### 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

### Is circuit-breakers or LlamaFactory more popular on GitHub?

LlamaFactory has more GitHub stars (73,157 vs 265). Stars measure visibility, not whether either tool fits your constraints.

### Are circuit-breakers and LlamaFactory open source?

Yes - both are open-source projects on GitHub (circuit-breakers: MIT, LlamaFactory: Apache-2.0).

### Where can I find alternatives to circuit-breakers or LlamaFactory?

GraphCanon lists graph-backed alternatives at [circuit-breakers alternatives](/tools/grayswanai-circuit-breakers/alternatives) and [LlamaFactory alternatives](/tools/hiyouga-llamafactory/alternatives) ([circuit-breakers markdown twin](/tools/grayswanai-circuit-breakers/alternatives.md), [LlamaFactory markdown twin](/tools/hiyouga-llamafactory/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/grayswanai-circuit-breakers-vs-hiyouga-llamafactory.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, circuit-breakers or LlamaFactory?

circuit-breakers: Dormant. LlamaFactory: 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 circuit-breakers and LlamaFactory?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [circuit-breakers trust report](/tools/grayswanai-circuit-breakers/trust); [LlamaFactory trust report](/tools/hiyouga-llamafactory/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=grayswanai-circuit-breakers`](/api/graphcanon/graph?tool=grayswanai-circuit-breakers)
- 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/_
