Comparison
LlamaFactory vs llm-pruning-collection
Verdict
Pick LlamaFactory when tags unique to LlamaFactory: agent, ai, deepseek, fine-tuning; pick llm-pruning-collection when tags unique to llm-pruning-collection: jax, llm-evaluation, llm-training, pruning.
Markdown twin · LlamaFactory alternatives · llm-pruning-collection alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | LlamaFactory | llm-pruning-collection |
|---|---|---|
| Maintenance | Very active (0d since push) As of 4d · github_public_v1 | Steady (85d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Personal account As of 4d · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 4d · osv@v1 | No lockfile (source not queried) As of today · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- LlamaFactory
- Unified Efficient Fine-Tuning of 100+ LLMs & VLMs
- llm-pruning-collection
- A collection of various llm pruning implementations, training code for GPUs & TPUs, and evaluation script.
Stars
- LlamaFactory
- 73k
- llm-pruning-collection
- 69
Forks
- LlamaFactory
- 8.9k
- llm-pruning-collection
- 8
Open issues
- LlamaFactory
- 1.1k
- llm-pruning-collection
- 2
Language
- LlamaFactory
- Python
- llm-pruning-collection
- 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.
- llm-pruning-collection
- -
Persona
- LlamaFactory
- -
- llm-pruning-collection
- -
Runtime
- LlamaFactory
- -
- llm-pruning-collection
- -
License
- LlamaFactory
- Apache-2.0
- llm-pruning-collection
- Apache-2.0
Last pushed
- LlamaFactory
- Jul 10, 2026
- llm-pruning-collection
- Apr 20, 2026
Categories
- LlamaFactory
- LLM Frameworks, Model Training
- llm-pruning-collection
- Developer Tools, LLM Frameworks, Model Training
Trust and health
Maintenance
- LlamaFactory
- Very active (96%)
- llm-pruning-collection
- Steady (60%)
Days since push
- LlamaFactory
- 0d
- llm-pruning-collection
- 85d
Open issues (now)
- LlamaFactory
- 1.1k
- llm-pruning-collection
- 2
Owner type
- LlamaFactory
- User
- llm-pruning-collection
- Organization
Full report
- LlamaFactory
- Trust report
- llm-pruning-collection
- Trust report
Choose LlamaFactory if…
- 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.
- More GitHub stars (73k vs 69) - visibility, not fit.
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 llm-pruning-collection if…
- Tags unique to llm-pruning-collection: jax, llm-evaluation, llm-training, pruning.
- Also covers Developer Tools.
- Leaner open-issue backlog (2).
When NOT to use llm-pruning-collection
- Developer Tools: A gateway is overkill when you're pinned to a single provider and model.
- 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 (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 (zlab-princeton/llm-pruning-collection) · observed Jul 15, 2026
- GitHub forks (zlab-princeton/llm-pruning-collection) · observed Jul 15, 2026
- Last push (zlab-princeton/llm-pruning-collection) · observed Apr 20, 2026
- License file (Apache-2.0) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: LlamaFactory 73k · llm-pruning-collection 69 (synced Jul 11, 2026).
Common questions
- What is the difference between LlamaFactory and llm-pruning-collection?
- LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. llm-pruning-collection: A collection of various llm pruning implementations, training code for GPUs & TPUs, and evaluation script.. See the comparison table for live GitHub stats and shared categories.
- When should I choose LlamaFactory over llm-pruning-collection?
- Choose LlamaFactory over llm-pruning-collection when 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; More GitHub stars (73k vs 69) - visibility, not fit.
- When should I choose llm-pruning-collection over LlamaFactory?
- Choose llm-pruning-collection over LlamaFactory when Tags unique to llm-pruning-collection: jax, llm-evaluation, llm-training, pruning; Also covers Developer Tools; Leaner open-issue backlog (2).
- 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 llm-pruning-collection?
- Developer Tools: A gateway is overkill when you're pinned to a single provider and model. 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 llm-pruning-collection more popular on GitHub?
- LlamaFactory has more GitHub stars (73,157 vs 69). Stars measure visibility, not whether either tool fits your constraints.
- Are LlamaFactory and llm-pruning-collection open source?
- Yes - both are open-source projects on GitHub (LlamaFactory: Apache-2.0, llm-pruning-collection: Apache-2.0).
- Where can I find alternatives to LlamaFactory or llm-pruning-collection?
- GraphCanon lists graph-backed alternatives at LlamaFactory alternatives and llm-pruning-collection alternatives (LlamaFactory markdown twin, llm-pruning-collection 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 llm-pruning-collection?
- LlamaFactory: Very active. llm-pruning-collection: Steady. 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 llm-pruning-collection?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LlamaFactory trust report; llm-pruning-collection trust report.