--- title: "LlamaFactory vs qa_metrics" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hiyouga-llamafactory-vs-zli12321-qa-metrics" tools: ["hiyouga-llamafactory", "zli12321-qa-metrics"] --- # LlamaFactory vs qa_metrics *GraphCanon updated Jul 15, 2026* ## Verdict Pick LlamaFactory when license: LlamaFactory is Apache-2.0, qa_metrics is MIT; pick qa_metrics when license: qa_metrics is MIT, LlamaFactory is Apache-2.0. [LlamaFactory](https://llamafactory.readthedocs.io) reports 73k GitHub stars, 8.9k forks, and 1.1k open issues, last pushed Jul 10, 2026. [qa_metrics](https://github.com/zli12321/qa_metrics) has 61 stars, 6 forks, and 0 open issues, last pushed Jul 18, 2025. Figures are from public GitHub metadata via [LlamaFactory's repository](https://github.com/hiyouga/LlamaFactory) and [qa_metrics's repository](https://github.com/zli12321/qa_metrics). | | [LlamaFactory](/tools/hiyouga-llamafactory.md) | [qa_metrics](/tools/zli12321-qa-metrics.md) | | --- | --- | --- | | Tagline | Unified Efficient Fine-Tuning of 100+ LLMs & VLMs | An easy python package to run quick basic QA evaluations. This package includes standardized QA evaluation metrics and semantic evaluation metrics: Black-box and Open-Source large language model promp | | Stars | 73,157 | 61 | | Forks | 8,937 | 6 | | Open issues | 1,067 | 0 | | Language | Python | 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 | Apache-2.0 | MIT | | Categories | LLM Frameworks, Model Training | Developer Tools, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [LlamaFactory](/tools/hiyouga-llamafactory.md) | [qa_metrics](/tools/zli12321-qa-metrics.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 361d | | Open issues (now) | 1.1k | 0 | | Full report | [trust report](/tools/hiyouga-llamafactory/trust.md) | [trust report](/tools/zli12321-qa-metrics/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 LlamaFactory if… - License: LlamaFactory is Apache-2.0, qa_metrics 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. ### Choose qa_metrics if… - License: qa_metrics is MIT, LlamaFactory is Apache-2.0. - Tags unique to qa_metrics: exact-matching, llm, llm-evaluation, llm-evaluation-framework. - Also covers Developer Tools. ## 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 ## When NOT to use qa_metrics - Last GitHub push was 361 days ago (slowing maintenance, Jul 18, 2025). Validate activity before betting a new project on qa_metrics. - 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. ## Common questions ### What is the difference between LlamaFactory and qa_metrics? LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. qa_metrics: An easy python package to run quick basic QA evaluations. This package includes standardized QA evaluation metrics and semantic evaluation metrics: Black-box and Open-Source large language model promp. See the comparison table for live GitHub stats and shared categories. ### When should I choose LlamaFactory over qa_metrics? Choose LlamaFactory over qa_metrics when License: LlamaFactory is Apache-2.0, qa_metrics 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 qa_metrics over LlamaFactory? Choose qa_metrics over LlamaFactory when License: qa_metrics is MIT, LlamaFactory is Apache-2.0; Tags unique to qa_metrics: exact-matching, llm, llm-evaluation, llm-evaluation-framework; Also covers Developer Tools. ### 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 qa_metrics? Last GitHub push was 361 days ago (slowing maintenance, Jul 18, 2025). Validate activity before betting a new project on qa_metrics. 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 qa_metrics more popular on GitHub? LlamaFactory has more GitHub stars (73,157 vs 61). Stars measure visibility, not whether either tool fits your constraints. ### Are LlamaFactory and qa_metrics open source? Yes - both are open-source projects on GitHub (LlamaFactory: Apache-2.0, qa_metrics: MIT). ### Where can I find alternatives to LlamaFactory or qa_metrics? GraphCanon lists graph-backed alternatives at [LlamaFactory alternatives](/tools/hiyouga-llamafactory/alternatives) and [qa_metrics alternatives](/tools/zli12321-qa-metrics/alternatives) ([LlamaFactory markdown twin](/tools/hiyouga-llamafactory/alternatives.md), [qa_metrics markdown twin](/tools/zli12321-qa-metrics/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/hiyouga-llamafactory-vs-zli12321-qa-metrics.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, LlamaFactory or qa_metrics? LlamaFactory: Very active. qa_metrics: Slowing. 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 qa_metrics? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [LlamaFactory trust report](/tools/hiyouga-llamafactory/trust); [qa_metrics trust report](/tools/zli12321-qa-metrics/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=hiyouga-llamafactory`](/api/graphcanon/graph?tool=hiyouga-llamafactory) - 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/_