Comparison
TinyEngram vs LlamaFactory
Verdict
Pick TinyEngram when tags unique to TinyEngram: deepseek-ai, engram, llm, llm-memory; pick LlamaFactory when tags unique to LlamaFactory: agent, ai, gemma, gpt.
Markdown twin · TinyEngram alternatives · LlamaFactory alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | TinyEngram | LlamaFactory |
|---|---|---|
| Maintenance | Steady (51d since push) As of today · github_public_v1 | Very active (0d since push) As of 1d · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Personal account As of 1d · github_public_v1 |
| Security (OSV) | No lockfile As of today · none | No lockfile As of 1d · none |
Tagline
- TinyEngram
- Research of DeepSeek Engram Architecture based on Qwen-3 and Stable Diffusion series.
- LlamaFactory
- Unified Efficient Fine-Tuning of 100+ LLMs & VLMs
Stars
- TinyEngram
- 736
- LlamaFactory
- 73k
Forks
- TinyEngram
- 51
- LlamaFactory
- 8.9k
Open issues
- TinyEngram
- 10
- LlamaFactory
- 1.1k
Language
- TinyEngram
- Python
- LlamaFactory
- Python
Adopt for
- TinyEngram
- -
- 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
- TinyEngram
- -
- LlamaFactory
- -
Runtime
- TinyEngram
- -
- LlamaFactory
- -
License
- TinyEngram
- -
- LlamaFactory
- Apache-2.0
Last pushed
- TinyEngram
- May 21, 2026
- LlamaFactory
- Jul 10, 2026
Categories
- TinyEngram
- Computer Vision, LLM Frameworks, Model Training
- LlamaFactory
- LLM Frameworks, Model Training
Trust and health
Maintenance
- TinyEngram
- Steady (60%)
- LlamaFactory
- Very active (96%)
Days since push
- TinyEngram
- 51d
- LlamaFactory
- 0d
Open issues (now)
- TinyEngram
- 10
- LlamaFactory
- 1.1k
Owner type
- TinyEngram
- Organization
- LlamaFactory
- User
Full report
- TinyEngram
- Trust report
- LlamaFactory
- Trust report
Choose TinyEngram if…
- Tags unique to TinyEngram: deepseek-ai, engram, llm, llm-memory.
- Also covers Computer Vision.
- Leaner open-issue backlog (10).
When NOT to use TinyEngram
- 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.
Choose LlamaFactory if…
- Tags unique to LlamaFactory: agent, ai, gemma, gpt.
- When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA.
- More GitHub stars (73k vs 736) - 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
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (AutoArk/TinyEngram) · observed Jul 11, 2026
- GitHub forks (AutoArk/TinyEngram) · observed Jul 11, 2026
- Last push (AutoArk/TinyEngram) · observed May 21, 2026
- License file (unknown) · 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: TinyEngram 736 · LlamaFactory 73k (synced Jul 11, 2026).
Common questions
- What is the difference between TinyEngram and LlamaFactory?
- TinyEngram: Research of DeepSeek Engram Architecture based on Qwen-3 and Stable Diffusion series.. LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. See the comparison table for live GitHub stats and shared categories.
- When should I choose TinyEngram over LlamaFactory?
- Choose TinyEngram over LlamaFactory when Tags unique to TinyEngram: deepseek-ai, engram, llm, llm-memory; Also covers Computer Vision; Leaner open-issue backlog (10).
- When should I choose LlamaFactory over TinyEngram?
- Choose LlamaFactory over TinyEngram when Tags unique to LlamaFactory: agent, ai, gemma, gpt; When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA; More GitHub stars (73k vs 736) - visibility, not fit.
- When should I avoid TinyEngram?
- 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.
- 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 TinyEngram or LlamaFactory more popular on GitHub?
- LlamaFactory has more GitHub stars (73,157 vs 736). Stars measure visibility, not whether either tool fits your constraints.
- Are TinyEngram and LlamaFactory open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to TinyEngram or LlamaFactory?
- GraphCanon lists graph-backed alternatives at TinyEngram alternatives and LlamaFactory alternatives (TinyEngram 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, TinyEngram or LlamaFactory?
- TinyEngram: 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 TinyEngram and LlamaFactory?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: TinyEngram trust report; LlamaFactory trust report.