Comparison
LlamaFactory vs StyleTTS2
Verdict
Pick LlamaFactory when license: LlamaFactory is Apache-2.0, StyleTTS2 is MIT; pick StyleTTS2 when license: StyleTTS2 is MIT, LlamaFactory is Apache-2.0.
Markdown twin · LlamaFactory alternatives · StyleTTS2 alternatives
GraphCanon updated 1d
vs
Trust & integrity
| Signal | LlamaFactory | StyleTTS2 |
|---|---|---|
| Maintenance | Very active (0d since push) As of 1d · github_public_v1 | Dormant (700d since push) As of 1d · github_public_v1 |
| Provenance | Not a fork · Personal account As of 1d · github_public_v1 | Not a fork · Personal account As of 1d · github_public_v1 |
| Security (OSV) | No lockfile As of 1d · none | No criticals As of 1d · osv@v1 |
Tagline
- LlamaFactory
- Unified Efficient Fine-Tuning of 100+ LLMs & VLMs
- StyleTTS2
- StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models
Stars
- LlamaFactory
- 73k
- StyleTTS2
- 6.3k
Forks
- LlamaFactory
- 8.9k
- StyleTTS2
- 694
Open issues
- LlamaFactory
- 1.1k
- StyleTTS2
- 118
Language
- LlamaFactory
- Python
- StyleTTS2
- 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.
- StyleTTS2
- -
Persona
- LlamaFactory
- -
- StyleTTS2
- -
Runtime
- LlamaFactory
- -
- StyleTTS2
- -
License
- LlamaFactory
- Apache-2.0
- StyleTTS2
- MIT
Last pushed
- LlamaFactory
- Jul 10, 2026
- StyleTTS2
- Aug 10, 2024
Categories
- LlamaFactory
- LLM Frameworks, Model Training
- StyleTTS2
- LLM Frameworks, Model Training, Vector Databases
Trust and health
Maintenance
- LlamaFactory
- Very active (96%)
- StyleTTS2
- Dormant (18%)
Days since push
- LlamaFactory
- 0d
- StyleTTS2
- 700d
Open issues (now)
- LlamaFactory
- 1.1k
- StyleTTS2
- 118
Security scan
- LlamaFactory
- No lockfile
- StyleTTS2
- No criticals
Full report
- LlamaFactory
- Trust report
- StyleTTS2
- Trust report
Choose LlamaFactory if…
- License: LlamaFactory is Apache-2.0, StyleTTS2 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 StyleTTS2 if…
- License: StyleTTS2 is MIT, LlamaFactory is Apache-2.0.
- Tags unique to StyleTTS2: adversarial-training, deep-learning, diffusion-models, gan.
- Also covers Vector Databases.
When NOT to use StyleTTS2
- Last GitHub push was 701 days ago (dormant maintenance, Aug 10, 2024). Validate activity before betting a new project on StyleTTS2.
- 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.
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 (yl4579/StyleTTS2) · observed Jul 11, 2026
- GitHub forks (yl4579/StyleTTS2) · observed Jul 11, 2026
- Last push (yl4579/StyleTTS2) · observed Aug 10, 2024
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: LlamaFactory 73k · StyleTTS2 6.3k (synced Jul 11, 2026).
Common questions
- What is the difference between LlamaFactory and StyleTTS2?
- LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. StyleTTS2: StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models. See the comparison table for live GitHub stats and shared categories.
- When should I choose LlamaFactory over StyleTTS2?
- Choose LlamaFactory over StyleTTS2 when License: LlamaFactory is Apache-2.0, StyleTTS2 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 StyleTTS2 over LlamaFactory?
- Choose StyleTTS2 over LlamaFactory when License: StyleTTS2 is MIT, LlamaFactory is Apache-2.0; Tags unique to StyleTTS2: adversarial-training, deep-learning, diffusion-models, gan; Also covers Vector Databases.
- 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 StyleTTS2?
- Last GitHub push was 701 days ago (dormant maintenance, Aug 10, 2024). Validate activity before betting a new project on StyleTTS2. 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.
- Is LlamaFactory or StyleTTS2 more popular on GitHub?
- LlamaFactory has more GitHub stars (73,157 vs 6,306). Stars measure visibility, not whether either tool fits your constraints.
- Are LlamaFactory and StyleTTS2 open source?
- Yes - both are open-source projects on GitHub (LlamaFactory: Apache-2.0, StyleTTS2: MIT).
- Where can I find alternatives to LlamaFactory or StyleTTS2?
- GraphCanon lists graph-backed alternatives at LlamaFactory alternatives and StyleTTS2 alternatives (LlamaFactory markdown twin, StyleTTS2 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 StyleTTS2?
- LlamaFactory: Very active. StyleTTS2: 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 StyleTTS2?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LlamaFactory trust report; StyleTTS2 trust report.