Home/Compare/LlamaFactory vs magicoder

Comparison

LlamaFactory vs magicoder

Verdict

Pick LlamaFactory when license: LlamaFactory is Apache-2.0, magicoder is MIT; pick magicoder when license: magicoder is MIT, LlamaFactory is Apache-2.0.

Markdown twin · LlamaFactory alternatives · magicoder alternatives

GraphCanon updated today

LlamaFactory logo

LlamaFactory

hiyouga/LlamaFactory

73kpushed Jul 10, 2026
vs
magicoder logo

magicoder

ise-uiuc/magicoder

2.1kpushed Nov 1, 2024

Trust & integrity

SignalLlamaFactorymagicoder
Maintenance
Very active (0d since push)
As of today · github_public_v1
Dormant (617d since push)
As of today · github_public_v1
Provenance
Not a fork · Personal account
As of today · github_public_v1
Not a fork · Organization 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
magicoder
[ICML'24] Magicoder: Empowering Code Generation with OSS-Instruct

Stars

LlamaFactory
73k
magicoder
2.1k

Forks

LlamaFactory
8.9k
magicoder
171

Open issues

LlamaFactory
1.1k
magicoder
4

Language

LlamaFactory
Python
magicoder
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.
magicoder
-

Persona

LlamaFactory
-
magicoder
-

Runtime

LlamaFactory
-
magicoder
-

License

LlamaFactory
Apache-2.0
magicoder
MIT

Last pushed

LlamaFactory
Jul 10, 2026
magicoder
Nov 1, 2024

Categories

LlamaFactory
LLM Frameworks, Model Training
magicoder
Data & Retrieval, LLM Frameworks, Model Training

Trust and health

Maintenance

LlamaFactory
Very active (96%)
magicoder
Dormant (18%)

Days since push

LlamaFactory
0d
magicoder
617d

Open issues (now)

LlamaFactory
1.1k
magicoder
4

Owner type

LlamaFactory
User
magicoder
Organization

Full report

LlamaFactory
Trust report
magicoder
Trust report

Choose LlamaFactory if…

  • License: LlamaFactory is Apache-2.0, magicoder is MIT.
  • Tags unique to LlamaFactory: agent, ai, deepseek, fine-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

Choose magicoder if…

  • License: magicoder is MIT, LlamaFactory is Apache-2.0.
  • Tags unique to magicoder: ai4code, llm, llm4code, python.
  • Also covers Data & Retrieval.

When NOT to use magicoder

  • Last GitHub push was 617 days ago (dormant maintenance, Nov 1, 2024). Validate activity before betting a new project on magicoder.
  • Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough.
  • 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 on cards: LlamaFactory 73k · magicoder 2.1k (synced Jul 11, 2026).

Common questions

What is the difference between LlamaFactory and magicoder?
LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. magicoder: [ICML'24] Magicoder: Empowering Code Generation with OSS-Instruct. See the comparison table for live GitHub stats and shared categories.
When should I choose LlamaFactory over magicoder?
Choose LlamaFactory over magicoder when License: LlamaFactory is Apache-2.0, magicoder is MIT; Tags unique to LlamaFactory: agent, ai, deepseek, fine-tuning; When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA.
When should I choose magicoder over LlamaFactory?
Choose magicoder over LlamaFactory when License: magicoder is MIT, LlamaFactory is Apache-2.0; Tags unique to magicoder: ai4code, llm, llm4code, python; Also covers Data & Retrieval.
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 magicoder?
Last GitHub push was 617 days ago (dormant maintenance, Nov 1, 2024). Validate activity before betting a new project on magicoder. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. 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 magicoder more popular on GitHub?
LlamaFactory has more GitHub stars (73,157 vs 2,096). Stars measure visibility, not whether either tool fits your constraints.
Are LlamaFactory and magicoder open source?
Yes - both are open-source projects on GitHub (LlamaFactory: Apache-2.0, magicoder: MIT).
Where can I find alternatives to LlamaFactory or magicoder?
GraphCanon lists graph-backed alternatives at LlamaFactory alternatives and magicoder alternatives (LlamaFactory markdown twin, magicoder 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 magicoder?
LlamaFactory: Very active. magicoder: 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 LlamaFactory and magicoder?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LlamaFactory trust report; magicoder trust report.