--- title: "Video-LLaMA vs LlamaFactory" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/damo-nlp-sg-video-llama-vs-hiyouga-llamafactory" tools: ["damo-nlp-sg-video-llama", "hiyouga-llamafactory"] --- # Video-LLaMA vs LlamaFactory Neutral, constraint-first comparison with live GitHub stats. | | [Video-LLaMA](/tools/damo-nlp-sg-video-llama.md) | [LlamaFactory](/tools/hiyouga-llamafactory.md) | | --- | --- | --- | | Tagline | Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding | Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024) | | Stars | 3,142 | 73,068 | | Forks | 286 | 8,931 | | Open issues | 69 | 1,063 | | Language | Python | Python | | Adopt for | Video-LLaMA is an instruction-tuned model for understanding videos using audio-visual information, available in Python with the BSD-3-Clause license. It specializes in integrating video and audio into large language-mods | Decision-critical facts about LlamaFactory. | | Persona | - | - | | Runtime | - | - | | License | BSD-3-Clause | Apache-2.0 | | Categories | Model Training, Computer Vision | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Video-LLaMA](/tools/damo-nlp-sg-video-llama.md) | [LlamaFactory](/tools/hiyouga-llamafactory.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 764d | 0d | | Open issues (now) | 69 | 1.1k | | Owner type | Organization | User | | Security scan | Not scanned | No lockfile | | Full report | [trust report](/tools/damo-nlp-sg-video-llama/trust.md) | [trust report](/tools/hiyouga-llamafactory/trust.md) | **Typed relationship:** Video-LLaMA _(successor)_ LlamaFactory Video-LLaMA builds on the fine-tuning capabilities of Llamafactory for audio-visual language model training, albeit in a more specialized video context. Coexists - LlamaFactory offers general fine-tuning capability but Video-LLaMA specializes in media content. ## Decision facts: Video-LLaMA - **Adopt for:** Video-LLaMA is an instruction-tuned model for understanding videos using audio-visual information, available in Python with the BSD-3-Clause license. It specializes in integrating video and audio into large language-mods ## Decision facts: LlamaFactory - **Adopt for:** Decision-critical facts about LlamaFactory. ## Choose when ### Choose Video-LLaMA if… - License: Video-LLaMA is BSD-3-Clause, LlamaFactory is Apache-2.0. - Video-LLaMA builds on the fine-tuning capabilities of Llamafactory for audio-visual language model training, albeit in a more specialized video context. - Tags unique to Video-LLaMA: video-language-pretraining, blip2, multi-modal-chatgpt, cross-modal-pretraining. - Also covers Computer Vision. - - You need a tool specifically designed to comprehend both the visual and audio elements of videos. ### Choose LlamaFactory if… - License: LlamaFactory is Apache-2.0, Video-LLaMA is BSD-3-Clause. - Video-LLaMA builds on the fine-tuning capabilities of Llamafactory for audio-visual language model training, albeit in a more specialized video context. - Tags unique to LlamaFactory: fine-tuning, deepseek, ai, instruction-tuning. - Also covers LLM Frameworks. - LlamaFactory is ideal when you need to fine-tune a wide variety of large language models (LLMs) and vision-language models (VLMs), with support for over 100 different models. ## When NOT to use Video-LLaMA - - If real-time audio support is essential, as it currently only supports Vicuna-7B and there are known issues on specific hardware like A10-24G. - - The online interactive demo may not handle Chinese text well due to the limitations of Vicuna/LLaMA for non-English texts. - - When looking for a more straightforward setup or integration, as Video-LLaMA might still require additional configuration (especially if running on certain hardware). ## When NOT to use LlamaFactory - LlamaFactory might not be the best choice if you're looking for real-time model deployment capabilities out-of-the-box without additional configurations or integrations beyond what it offers (e.g., in - more real-time critical applications where direct deployment frameworks are preferred). - If your project does not require extensive support from the community of LLaMA users and partners like Amazon, NVIDIA, or Aliyun, you may find other tools more suitable due to potentially fewer integr ## Common questions ### What is the difference between Video-LLaMA and LlamaFactory? Video-LLaMA: Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding. LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024). See the comparison table for live GitHub stats and shared categories. ### When should I choose Video-LLaMA over LlamaFactory? Choose Video-LLaMA over LlamaFactory when License: Video-LLaMA is BSD-3-Clause, LlamaFactory is Apache-2.0; Video-LLaMA builds on the fine-tuning capabilities of Llamafactory for audio-visual language model training, albeit in a more specialized video context; Tags unique to Video-LLaMA: video-language-pretraining, blip2, multi-modal-chatgpt, cross-modal-pretraining; Also covers Computer Vision; - You need a tool specifically designed to comprehend both the visual and audio elements of videos. ### When should I choose LlamaFactory over Video-LLaMA? Choose LlamaFactory over Video-LLaMA when License: LlamaFactory is Apache-2.0, Video-LLaMA is BSD-3-Clause; Video-LLaMA builds on the fine-tuning capabilities of Llamafactory for audio-visual language model training, albeit in a more specialized video context; Tags unique to LlamaFactory: fine-tuning, deepseek, ai, instruction-tuning; Also covers LLM Frameworks; LlamaFactory is ideal when you need to fine-tune a wide variety of large language models (LLMs) and vision-language models (VLMs), with support for over 100 different models. ### When should I avoid Video-LLaMA? - If real-time audio support is essential, as it currently only supports Vicuna-7B and there are known issues on specific hardware like A10-24G. - The online interactive demo may not handle Chinese text well due to the limitations of Vicuna/LLaMA for non-English texts. - When looking for a more straightforward setup or integration, as Video-LLaMA might still require additional configuration (especially if running on certain hardware). ### When should I avoid LlamaFactory? LlamaFactory might not be the best choice if you're looking for real-time model deployment capabilities out-of-the-box without additional configurations or integrations beyond what it offers (e.g., in more real-time critical applications where direct deployment frameworks are preferred). If your project does not require extensive support from the community of LLaMA users and partners like Amazon, NVIDIA, or Aliyun, you may find other tools more suitable due to potentially fewer integr ### Is Video-LLaMA or LlamaFactory more popular on GitHub? LlamaFactory has more GitHub stars (73,068 vs 3,142). Stars measure visibility, not whether either tool fits your constraints. ### Are Video-LLaMA and LlamaFactory open source? Yes - both are open-source projects on GitHub (Video-LLaMA: BSD-3-Clause, LlamaFactory: Apache-2.0). ### Where can I find alternatives to Video-LLaMA or LlamaFactory? GraphCanon lists graph-backed alternatives at /tools/damo-nlp-sg-video-llama/alternatives and /tools/hiyouga-llamafactory/alternatives (/tools/damo-nlp-sg-video-llama/alternatives.md, /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 /compare/damo-nlp-sg-video-llama-vs-hiyouga-llamafactory.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Video-LLaMA or LlamaFactory? Video-LLaMA: 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 Video-LLaMA and LlamaFactory? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Video-LLaMA: /tools/damo-nlp-sg-video-llama/trust; LlamaFactory: /tools/hiyouga-llamafactory/trust. --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=damo-nlp-sg-video-llama`](/api/graphcanon/graph?tool=damo-nlp-sg-video-llama) - 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/_