Comparison
LlamaFactory vs MiniMax-01
Verdict
Pick LlamaFactory if 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; pick MiniMax-01 if miniMax-01 optimizes Linear Attention for large-language and vision-language models.
Markdown twin · LlamaFactory alternatives · MiniMax-01 alternatives
GraphCanon updated 5d
Trust & integrity
| Signal | LlamaFactory | MiniMax-01 |
|---|---|---|
| Maintenance | Very active (2d since push) As of 6d · github_public_v1 | Dormant (406d since push) As of 5d · github_public_v1 |
| Provenance | Not a fork · Personal account As of 6d · github_public_v1 | Not a fork · Organization account As of 5d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · 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
- MiniMax-01
- Repository for MiniMax-Text-01 and MiniMax-VL-01 models based on Linear Attention
Stars
- LlamaFactory
- 74k
- MiniMax-01
- 3.5k
Forks
- LlamaFactory
- 9.1k
- MiniMax-01
- 332
Open issues
- LlamaFactory
- 1.1k
- MiniMax-01
- 8
Language
- LlamaFactory
- Python
- MiniMax-01
- 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.
- MiniMax-01
- MiniMax-01 optimizes Linear Attention for large-language and vision-language models.
Persona
- LlamaFactory
- -
- MiniMax-01
- -
Runtime
- LlamaFactory
- -
- MiniMax-01
- -
License
- LlamaFactory
- Apache-2.0
- MiniMax-01
- MIT
Last pushed
- LlamaFactory
- Aug 13, 2026
- MiniMax-01
- Jul 7, 2025
Categories
- LlamaFactory
- LLM Frameworks, Model Training
- MiniMax-01
- LLM Frameworks, Model Training
Trust and health
Maintenance
- LlamaFactory
- Very active (96%)
- MiniMax-01
- Dormant (18%)
Days since push
- LlamaFactory
- 2d
- MiniMax-01
- 406d
Open issues (now)
- LlamaFactory
- 1.1k
- MiniMax-01
- 8
Stars delta
- LlamaFactory
- +803 (30d)
- MiniMax-01
- +17 (30d)
Open issues delta
- LlamaFactory
- +39 (30d)
- MiniMax-01
- 0 (30d)
Owner type
- LlamaFactory
- User
- MiniMax-01
- Organization
Full report
- LlamaFactory
- Trust report
- MiniMax-01
- Trust report
Typed relationship
Choose LlamaFactory if…
- License: LlamaFactory is Apache-2.0, MiniMax-01 is MIT.
- Both MiniMax-01 and LlamaFactory involve fine-tuning of large language models, but they serve as different implementations for similar purposes.
- 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 MiniMax-01 if…
- License: MiniMax-01 is MIT, LlamaFactory is Apache-2.0.
- Both MiniMax-01 and LlamaFactory involve fine-tuning of large language models, but they serve as different implementations for similar purposes.
- Tags unique to MiniMax-01: llm, vision-language-model, vlm.
- When high throughput performance is required for model serving
When NOT to use MiniMax-01
- If deep customization of attention mechanisms aside from Linear Attention is needed
- In favor of frameworks lacking vLLM's optimization features, when efficiency or memory use are secondary to flexibility
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 Aug 16, 2026
- GitHub forks (hiyouga/LlamaFactory) · observed Aug 16, 2026
- Last push (hiyouga/LlamaFactory) · observed Aug 13, 2026
- License file (Apache-2.0) · observed Aug 16, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (MiniMax-AI/MiniMax-01) · observed Aug 18, 2026
- GitHub forks (MiniMax-AI/MiniMax-01) · observed Aug 18, 2026
- Last push (MiniMax-AI/MiniMax-01) · observed Jul 7, 2025
- License file (MIT) · observed Aug 18, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: LlamaFactory 74k · MiniMax-01 3.5k (synced Aug 16, 2026).
Common questions
- What is the difference between LlamaFactory and MiniMax-01?
- LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. MiniMax-01: Repository for MiniMax-Text-01 and MiniMax-VL-01 models based on Linear Attention. See the comparison table for live GitHub stats and shared categories.
- When should I choose LlamaFactory over MiniMax-01?
- Choose LlamaFactory over MiniMax-01 when License: LlamaFactory is Apache-2.0, MiniMax-01 is MIT; Both MiniMax-01 and LlamaFactory involve fine-tuning of large language models, but they serve as different implementations for similar purposes; 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 MiniMax-01 over LlamaFactory?
- Choose MiniMax-01 over LlamaFactory when License: MiniMax-01 is MIT, LlamaFactory is Apache-2.0; Both MiniMax-01 and LlamaFactory involve fine-tuning of large language models, but they serve as different implementations for similar purposes; Tags unique to MiniMax-01: llm, vision-language-model, vlm; When high throughput performance is required for model serving.
- 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 MiniMax-01?
- If deep customization of attention mechanisms aside from Linear Attention is needed In favor of frameworks lacking vLLM's optimization features, when efficiency or memory use are secondary to flexibility
- Is LlamaFactory or MiniMax-01 more popular on GitHub?
- LlamaFactory has more GitHub stars (74,132 vs 3,463). Stars measure visibility, not whether either tool fits your constraints.
- Are LlamaFactory and MiniMax-01 open source?
- Yes - both are open-source projects on GitHub (LlamaFactory: Apache-2.0, MiniMax-01: MIT).
- Where can I find alternatives to LlamaFactory or MiniMax-01?
- GraphCanon lists graph-backed alternatives at LlamaFactory alternatives and MiniMax-01 alternatives (LlamaFactory markdown twin, MiniMax-01 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 MiniMax-01?
- LlamaFactory: Very active. MiniMax-01: 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 MiniMax-01?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LlamaFactory trust report; MiniMax-01 trust report.