--- title: "atlas vs LlamaFactory" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/avarok-cybersecurity-atlas-vs-hiyouga-llamafactory" tools: ["avarok-cybersecurity-atlas", "hiyouga-llamafactory"] --- # atlas vs LlamaFactory *GraphCanon updated Jul 11, 2026* ## Verdict Pick atlas when atlas is primarily Rust; LlamaFactory is Python; pick LlamaFactory when llamaFactory is primarily Python; atlas is Rust. [atlas](https://atlasinference.io) reports 588 GitHub stars, 83 forks, and 61 open issues, last pushed Jul 10, 2026. [LlamaFactory](https://llamafactory.readthedocs.io) has 73k stars, 8.9k forks, and 1.1k open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [atlas's repository](https://github.com/Avarok-Cybersecurity/atlas) and [LlamaFactory's repository](https://github.com/hiyouga/LlamaFactory). | | [atlas](/tools/avarok-cybersecurity-atlas.md) | [LlamaFactory](/tools/hiyouga-llamafactory.md) | | --- | --- | --- | | Tagline | Pure Rust Inference Engine | Unified Efficient Fine-Tuning of 100+ LLMs & VLMs | | Stars | 588 | 73,157 | | Forks | 83 | 8,937 | | Open issues | 61 | 1,067 | | Language | Rust | Python | | Adopt for | - | 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 | - | - | | Runtime | - | - | | License | AGPL-3.0 | Apache-2.0 | | Categories | Inference & Serving, LLM Frameworks, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [atlas](/tools/avarok-cybersecurity-atlas.md) | [LlamaFactory](/tools/hiyouga-llamafactory.md) | | --- | --- | --- | | Open issues (now) | 61 | 1.1k | | Owner type | Organization | User | | Full report | [trust report](/tools/avarok-cybersecurity-atlas/trust.md) | [trust report](/tools/hiyouga-llamafactory/trust.md) | ## Decision facts: LlamaFactory - **Adopt for:** 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. ## Choose when ### Choose atlas if… - atlas is primarily Rust; LlamaFactory is Python. - License: atlas is AGPL-3.0, LlamaFactory is Apache-2.0. - Tags unique to atlas: cuda, dgx, dgx-spark, gb10. - Also covers Inference & Serving. ### Choose LlamaFactory if… - LlamaFactory is primarily Python; atlas is Rust. - License: LlamaFactory is Apache-2.0, atlas is AGPL-3.0. - 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 atlas - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - 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 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 ## Common questions ### What is the difference between atlas and LlamaFactory? atlas: Pure Rust Inference Engine. LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. See the comparison table for live GitHub stats and shared categories. ### When should I choose atlas over LlamaFactory? Choose atlas over LlamaFactory when atlas is primarily Rust; LlamaFactory is Python; License: atlas is AGPL-3.0, LlamaFactory is Apache-2.0; Tags unique to atlas: cuda, dgx, dgx-spark, gb10; Also covers Inference & Serving. ### When should I choose LlamaFactory over atlas? Choose LlamaFactory over atlas when LlamaFactory is primarily Python; atlas is Rust; License: LlamaFactory is Apache-2.0, atlas is AGPL-3.0; 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 atlas? Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. 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 atlas or LlamaFactory more popular on GitHub? LlamaFactory has more GitHub stars (73,157 vs 588). Stars measure visibility, not whether either tool fits your constraints. ### Are atlas and LlamaFactory open source? Yes - both are open-source projects on GitHub (atlas: AGPL-3.0, LlamaFactory: Apache-2.0). ### Where can I find alternatives to atlas or LlamaFactory? GraphCanon lists graph-backed alternatives at [atlas alternatives](/tools/avarok-cybersecurity-atlas/alternatives) and [LlamaFactory alternatives](/tools/hiyouga-llamafactory/alternatives) ([atlas markdown twin](/tools/avarok-cybersecurity-atlas/alternatives.md), [LlamaFactory markdown twin](/tools/hiyouga-llamafactory/alternatives.md)), 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](/compare/avarok-cybersecurity-atlas-vs-hiyouga-llamafactory.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, atlas or LlamaFactory? atlas: Very active. 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 atlas and LlamaFactory? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [atlas trust report](/tools/avarok-cybersecurity-atlas/trust); [LlamaFactory trust report](/tools/hiyouga-llamafactory/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=avarok-cybersecurity-atlas`](/api/graphcanon/graph?tool=avarok-cybersecurity-atlas) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_