--- title: "lmql vs LlamaFactory" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/eth-sri-lmql-vs-hiyouga-llamafactory" tools: ["eth-sri-lmql", "hiyouga-llamafactory"] --- # lmql vs LlamaFactory *GraphCanon updated Jul 11, 2026* ## Verdict Pick lmql when tags unique to lmql: python, programming-language, chatgpt, huggingface; pick LlamaFactory when tags unique to LlamaFactory: gemma, fine-tuning, deepseek, ai. [lmql](https://lmql.ai) reports 4.2k GitHub stars, 220 forks, and 120 open issues, last pushed May 22, 2025. [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 [lmql's repository](https://github.com/eth-sri/lmql) and [LlamaFactory's repository](https://github.com/hiyouga/LlamaFactory). | | [lmql](/tools/eth-sri-lmql.md) | [LlamaFactory](/tools/hiyouga-llamafactory.md) | | --- | --- | --- | | Tagline | A language for constraint-guided and efficient LLM programming. | Unified Efficient Fine-Tuning of 100+ LLMs & VLMs | | Stars | 4,200 | 73,157 | | Forks | 220 | 8,937 | | Open issues | 120 | 1,067 | | 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 | Apache-2.0 | | Categories | LLM Frameworks, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [lmql](/tools/eth-sri-lmql.md) | [LlamaFactory](/tools/hiyouga-llamafactory.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 415d | 0d | | Open issues (now) | 120 | 1.1k | | Owner type | Organization | User | | Full report | [trust report](/tools/eth-sri-lmql/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 lmql if… - Tags unique to lmql: python, programming-language, chatgpt, huggingface. - Leaner open-issue backlog (120). ### Choose LlamaFactory if… - Tags unique to LlamaFactory: gemma, fine-tuning, deepseek, ai. - When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA. - More GitHub stars (73k vs 4.2k) - visibility, not fit. ## When NOT to use lmql - Last GitHub push was 416 days ago (dormant maintenance, May 22, 2025). Validate activity before betting a new project on lmql. - 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 lmql and LlamaFactory? lmql: A language for constraint-guided and efficient LLM programming.. LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. See the comparison table for live GitHub stats and shared categories. ### When should I choose lmql over LlamaFactory? Choose lmql over LlamaFactory when Tags unique to lmql: python, programming-language, chatgpt, huggingface; Leaner open-issue backlog (120). ### When should I choose LlamaFactory over lmql? Choose LlamaFactory over lmql when Tags unique to LlamaFactory: gemma, fine-tuning, deepseek, ai; When you need to fine-tune over 100 different LLMs or VLMs with efficient methods like LoRA or QLoRA; More GitHub stars (73k vs 4.2k) - visibility, not fit. ### When should I avoid lmql? Last GitHub push was 416 days ago (dormant maintenance, May 22, 2025). Validate activity before betting a new project on lmql. 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 lmql or LlamaFactory more popular on GitHub? LlamaFactory has more GitHub stars (73,157 vs 4,200). Stars measure visibility, not whether either tool fits your constraints. ### Are lmql and LlamaFactory open source? Yes - both are open-source projects on GitHub (lmql: Apache-2.0, LlamaFactory: Apache-2.0). ### Where can I find alternatives to lmql or LlamaFactory? GraphCanon lists graph-backed alternatives at [lmql alternatives](/tools/eth-sri-lmql/alternatives) and [LlamaFactory alternatives](/tools/hiyouga-llamafactory/alternatives) ([lmql markdown twin](/tools/eth-sri-lmql/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/eth-sri-lmql-vs-hiyouga-llamafactory.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, lmql or LlamaFactory? lmql: Dormant. 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 lmql and LlamaFactory? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [lmql trust report](/tools/eth-sri-lmql/trust); [LlamaFactory trust report](/tools/hiyouga-llamafactory/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=eth-sri-lmql`](/api/graphcanon/graph?tool=eth-sri-lmql) - 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/_