Comparison
octopack vs LlamaFactory
Verdict
Pick octopack when octopack is primarily Jupyter Notebook; LlamaFactory is Python; pick LlamaFactory when llamaFactory is primarily Python; octopack is Jupyter Notebook.
Markdown twin · octopack alternatives · LlamaFactory alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | octopack | LlamaFactory |
|---|---|---|
| Maintenance | Dormant (521d 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
- octopack
- 🐙 OctoPack: Instruction Tuning Code Large Language Models
- LlamaFactory
- Unified Efficient Fine-Tuning of 100+ LLMs & VLMs
Stars
- octopack
- 479
- LlamaFactory
- 73k
Forks
- octopack
- 29
- LlamaFactory
- 8.9k
Open issues
- octopack
- 14
- LlamaFactory
- 1.1k
Language
- octopack
- Jupyter Notebook
- LlamaFactory
- Python
Adopt for
- octopack
- -
- 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
- octopack
- -
- LlamaFactory
- -
Runtime
- octopack
- -
- LlamaFactory
- -
License
- octopack
- MIT
- LlamaFactory
- Apache-2.0
Last pushed
- octopack
- Feb 5, 2025
- LlamaFactory
- Jul 10, 2026
Categories
- octopack
- LLM Frameworks, Model Training, Vector Databases
- LlamaFactory
- LLM Frameworks, Model Training
Trust and health
Maintenance
- octopack
- Dormant (18%)
- LlamaFactory
- Very active (96%)
Days since push
- octopack
- 521d
- LlamaFactory
- 0d
Open issues (now)
- octopack
- 14
- LlamaFactory
- 1.1k
Owner type
- octopack
- Organization
- LlamaFactory
- User
Full report
- octopack
- Trust report
- LlamaFactory
- Trust report
Choose octopack if…
- octopack is primarily Jupyter Notebook; LlamaFactory is Python.
- License: octopack is MIT, LlamaFactory is Apache-2.0.
- Tags unique to octopack: jupyter notebook.
- Also covers Vector Databases.
When NOT to use octopack
- Last GitHub push was 521 days ago (dormant maintenance, Feb 5, 2025). Validate activity before betting a new project on octopack.
- 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.
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
Choose LlamaFactory if…
- LlamaFactory is primarily Python; octopack is Jupyter Notebook.
- License: LlamaFactory is Apache-2.0, octopack 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
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (bigcode-project/octopack) · observed Jul 11, 2026
- GitHub forks (bigcode-project/octopack) · observed Jul 11, 2026
- Last push (bigcode-project/octopack) · observed Feb 5, 2025
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- 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 on cards: octopack 479 · LlamaFactory 73k (synced Jul 11, 2026).
Common questions
- What is the difference between octopack and LlamaFactory?
- octopack: 🐙 OctoPack: Instruction Tuning Code Large Language Models. LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. See the comparison table for live GitHub stats and shared categories.
- When should I choose octopack over LlamaFactory?
- Choose octopack over LlamaFactory when octopack is primarily Jupyter Notebook; LlamaFactory is Python; License: octopack is MIT, LlamaFactory is Apache-2.0; Tags unique to octopack: jupyter notebook; Also covers Vector Databases.
- When should I choose LlamaFactory over octopack?
- Choose LlamaFactory over octopack when LlamaFactory is primarily Python; octopack is Jupyter Notebook; License: LlamaFactory is Apache-2.0, octopack 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 avoid octopack?
- Last GitHub push was 521 days ago (dormant maintenance, Feb 5, 2025). Validate activity before betting a new project on octopack. 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. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
- 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 octopack or LlamaFactory more popular on GitHub?
- LlamaFactory has more GitHub stars (73,157 vs 479). Stars measure visibility, not whether either tool fits your constraints.
- Are octopack and LlamaFactory open source?
- Yes - both are open-source projects on GitHub (octopack: MIT, LlamaFactory: Apache-2.0).
- Where can I find alternatives to octopack or LlamaFactory?
- GraphCanon lists graph-backed alternatives at octopack alternatives and LlamaFactory alternatives (octopack 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, octopack or LlamaFactory?
- octopack: 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 octopack and LlamaFactory?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: octopack trust report; LlamaFactory trust report.