Home/Compare/MetaClaw vs LlamaFactory

Comparison

MetaClaw vs LlamaFactory

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.

Markdown twin · MetaClaw alternatives · LlamaFactory alternatives

GraphCanon updated today

MetaClaw logo

MetaClaw

aiming-lab/MetaClaw

3.5kpushed Jun 7, 2026
vs
LlamaFactory logo

LlamaFactory

hiyouga/LlamaFactory

73kpushed Jul 10, 2026

Trust & integrity

SignalMetaClawLlamaFactory
Maintenance
Steady (34d since push)
As of today · github_public_v1
Very active (0d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization 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

MetaClaw
🦞 Just talk to your agent — it learns and EVOLVES 🧬.
LlamaFactory
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs

Stars

MetaClaw
3.5k
LlamaFactory
73k

Forks

MetaClaw
445
LlamaFactory
8.9k

Open issues

MetaClaw
16
LlamaFactory
1.1k

Language

MetaClaw
Python
LlamaFactory
Python

Adopt for

MetaClaw
-
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.

Persona

MetaClaw
-
LlamaFactory
-

Runtime

MetaClaw
-
LlamaFactory
-

License

MetaClaw
MIT
LlamaFactory
Apache-2.0

Last pushed

MetaClaw
Jun 7, 2026
LlamaFactory
Jul 10, 2026

Categories

MetaClaw
Model Training, LLM Frameworks, AI Agents
LlamaFactory
Model Training, LLM Frameworks

Trust and health

Maintenance

MetaClaw
Steady (60%)
LlamaFactory
Very active (96%)

Days since push

MetaClaw
34d
LlamaFactory
0d

Open issues (now)

MetaClaw
16
LlamaFactory
1.1k

Owner type

MetaClaw
Organization
LlamaFactory
User

Full report

MetaClaw
Trust report
LlamaFactory
Trust report

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.

When NOT to use MetaClaw

  • Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
  • AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.

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 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

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: MetaClaw 3.5k · LlamaFactory 73k (synced Jul 11, 2026).

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?
Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. 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 and LlamaFactory alternatives (MetaClaw markdown twin, LlamaFactory 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, 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; LlamaFactory trust report.