--- title: "MetaClaw vs LlamaFactory" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/aiming-lab-metaclaw-vs-hiyouga-llamafactory" tools: ["aiming-lab-metaclaw", "hiyouga-llamafactory"] --- # MetaClaw vs LlamaFactory *GraphCanon updated Jul 11, 2026* ## Verdict Pick MetaClaw when license: MetaClaw is MIT, LlamaFactory is Apache-2.0; pick LlamaFactory when license: LlamaFactory is Apache-2.0, MetaClaw is MIT. [MetaClaw](https://arxiv.org/abs/2603.17187) reports 3.5k GitHub stars, 445 forks, and 16 open issues, last pushed Jun 7, 2026. [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 [MetaClaw's repository](https://github.com/aiming-lab/MetaClaw) and [LlamaFactory's repository](https://github.com/hiyouga/LlamaFactory). | | [MetaClaw](/tools/aiming-lab-metaclaw.md) | [LlamaFactory](/tools/hiyouga-llamafactory.md) | | --- | --- | --- | | Tagline | 🦞 Just talk to your agent — it learns and EVOLVES 🧬. | Unified Efficient Fine-Tuning of 100+ LLMs & VLMs | | Stars | 3,466 | 73,157 | | Forks | 445 | 8,937 | | Open issues | 16 | 1,067 | | Language | Python | 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, AI Agents | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [MetaClaw](/tools/aiming-lab-metaclaw.md) | [LlamaFactory](/tools/hiyouga-llamafactory.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 34d | 0d | | Open issues (now) | 16 | 1.1k | | Owner type | Organization | User | | Full report | [trust report](/tools/aiming-lab-metaclaw/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 MetaClaw if… - License: MetaClaw is MIT, LlamaFactory is Apache-2.0. - Tags unique to MetaClaw: meta-learning, metaclaw, lora, llm. - Also covers AI Agents. ### Choose LlamaFactory if… - License: LlamaFactory is Apache-2.0, MetaClaw is MIT. - Tags unique to LlamaFactory: gemma, deepseek, ai, instruction-tuning. - When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA. ## When NOT to use MetaClaw - 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. - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. ## 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 MetaClaw and LlamaFactory? MetaClaw: 🦞 Just talk to your agent — it learns and EVOLVES 🧬.. LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. See the comparison table for live GitHub stats and shared categories. ### When should I choose MetaClaw over LlamaFactory? Choose MetaClaw over LlamaFactory when License: MetaClaw is MIT, LlamaFactory is Apache-2.0; Tags unique to MetaClaw: meta-learning, metaclaw, lora, llm; Also covers AI Agents. ### When should I choose LlamaFactory over MetaClaw? Choose LlamaFactory over MetaClaw when License: LlamaFactory is Apache-2.0, MetaClaw is MIT; Tags unique to LlamaFactory: gemma, deepseek, ai, instruction-tuning; When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA. ### When should I avoid MetaClaw? 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. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. ### 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 MetaClaw or LlamaFactory more popular on GitHub? LlamaFactory has more GitHub stars (73,157 vs 3,466). Stars measure visibility, not whether either tool fits your constraints. ### Are MetaClaw and LlamaFactory open source? Yes - both are open-source projects on GitHub (MetaClaw: MIT, LlamaFactory: Apache-2.0). ### Where can I find alternatives to MetaClaw or LlamaFactory? GraphCanon lists graph-backed alternatives at [MetaClaw alternatives](/tools/aiming-lab-metaclaw/alternatives) and [LlamaFactory alternatives](/tools/hiyouga-llamafactory/alternatives) ([MetaClaw markdown twin](/tools/aiming-lab-metaclaw/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/aiming-lab-metaclaw-vs-hiyouga-llamafactory.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, MetaClaw or LlamaFactory? MetaClaw: Steady. 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 MetaClaw and LlamaFactory? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [MetaClaw trust report](/tools/aiming-lab-metaclaw/trust); [LlamaFactory trust report](/tools/hiyouga-llamafactory/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=aiming-lab-metaclaw`](/api/graphcanon/graph?tool=aiming-lab-metaclaw) - 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/_