--- title: "Video-LLaMA vs Qwen" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/damo-nlp-sg-video-llama-vs-qwenlm-qwen" tools: ["damo-nlp-sg-video-llama", "qwenlm-qwen"] --- # Video-LLaMA vs Qwen Neutral, constraint-first comparison with live GitHub stats. | | [Video-LLaMA](/tools/damo-nlp-sg-video-llama.md) | [Qwen](/tools/qwenlm-qwen.md) | | --- | --- | --- | | Tagline | Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding | Official repo for Qwen, a Chinese large language model by Alibaba Cloud | | Stars | 3,142 | 21,404 | | Forks | 286 | 1,849 | | Open issues | 69 | 42 | | 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 | Qwen is a Chinese large language model developed by Alibaba Cloud, designed to support various formats and optimizations for natural language processing tasks. Though its official repository suggests it's no longer under | | Persona | - | - | | Runtime | - | - | | License | BSD-3-Clause | Apache-2.0 | | Categories | Model Training, Computer Vision | Model Training, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Video-LLaMA](/tools/damo-nlp-sg-video-llama.md) | [Qwen](/tools/qwenlm-qwen.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Slowing (36%) | | Days since push | 765d | 125d | | Open issues (now) | 69 | 42 | | Security scan | No lockfile | 44 low (44 low) | | Full report | [trust report](/tools/damo-nlp-sg-video-llama/trust.md) | [trust report](/tools/qwenlm-qwen/trust.md) | **Typed relationship:** Video-LLaMA _(alternative)_ Qwen Qwen is also a Chinese large language model, which makes it an alternative to Video-LLaMA for instruction-tuned models focusing on different modalities (video vs text mainly). ## 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: Qwen - **Pricing:** unknown - Pricing information is not specified in the repository and depends on usage via Alibaba Cloud or APIs like HuggingFace which have their own pricing structures for model usage. - **Adopt for:** Qwen is a Chinese large language model developed by Alibaba Cloud, designed to support various formats and optimizations for natural language processing tasks. Though its official repository suggests it's no longer under ## Choose when ### Choose Video-LLaMA if… - License: Video-LLaMA is BSD-3-Clause, Qwen is Apache-2.0. - Qwen is also a Chinese large language model, which makes it an alternative to Video-LLaMA for instruction-tuned models focusing on different modalities (video vs text mainly). - Tags unique to Video-LLaMA: video-language-pretraining, llama, blip2, multi-modal-chatgpt. - Also covers Computer Vision. - - You need a tool specifically designed to comprehend both the visual and audio elements of videos. ### Choose Qwen if… - License: Qwen is Apache-2.0, Video-LLaMA is BSD-3-Clause. - Pricing: Pricing information is not specified in the repository and depends on usage via Alibaba Cloud or APIs like HuggingFace which have their own pricing structures for model usage.. - Qwen is also a Chinese large language model, which makes it an alternative to Video-LLaMA for instruction-tuned models focusing on different modalities (video vs text mainly). - Tags unique to Qwen: pretrained-models, llm, natural-language-processing, flash-attention. - Also covers LLM Frameworks. - When focusing on applications that cater primarily to the Chinese-speaking audience as Qwen is specifically optimized for the Chinese language. ## 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 Qwen - For projects requiring ongoing maintenance support as the repository notes a move towards Qwen2, suggesting current versions have ceased active development. - In scenarios where absolute state-of-the-art performance and recent updates for all languages are critical, due to its focus on Chinese language applications and stated obsolescence. ## Common questions ### What is the difference between Video-LLaMA and Qwen? Video-LLaMA: Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding. Qwen: Official repo for Qwen, a Chinese large language model by Alibaba Cloud. See the comparison table for live GitHub stats and shared categories. ### When should I choose Video-LLaMA over Qwen? Choose Video-LLaMA over Qwen when License: Video-LLaMA is BSD-3-Clause, Qwen is Apache-2.0; Qwen is also a Chinese large language model, which makes it an alternative to Video-LLaMA for instruction-tuned models focusing on different modalities (video vs text mainly); Tags unique to Video-LLaMA: video-language-pretraining, llama, blip2, multi-modal-chatgpt; Also covers Computer Vision; - You need a tool specifically designed to comprehend both the visual and audio elements of videos. ### When should I choose Qwen over Video-LLaMA? Choose Qwen over Video-LLaMA when License: Qwen is Apache-2.0, Video-LLaMA is BSD-3-Clause; Pricing: Pricing information is not specified in the repository and depends on usage via Alibaba Cloud or APIs like HuggingFace which have their own pricing structures for model usage.; Qwen is also a Chinese large language model, which makes it an alternative to Video-LLaMA for instruction-tuned models focusing on different modalities (video vs text mainly); Tags unique to Qwen: pretrained-models, llm, natural-language-processing, flash-attention; Also covers LLM Frameworks; When focusing on applications that cater primarily to the Chinese-speaking audience as Qwen is specifically optimized for the Chinese language. ### 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 Qwen? For projects requiring ongoing maintenance support as the repository notes a move towards Qwen2, suggesting current versions have ceased active development. In scenarios where absolute state-of-the-art performance and recent updates for all languages are critical, due to its focus on Chinese language applications and stated obsolescence. ### Is Video-LLaMA or Qwen more popular on GitHub? Qwen has more GitHub stars (21,404 vs 3,142). Stars measure visibility, not whether either tool fits your constraints. ### Are Video-LLaMA and Qwen open source? Yes - both are open-source projects on GitHub (Video-LLaMA: BSD-3-Clause, Qwen: Apache-2.0). ### Where can I find alternatives to Video-LLaMA or Qwen? GraphCanon lists graph-backed alternatives at /tools/damo-nlp-sg-video-llama/alternatives and /tools/qwenlm-qwen/alternatives (/tools/damo-nlp-sg-video-llama/alternatives.md, /tools/qwenlm-qwen/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-qwenlm-qwen.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Video-LLaMA or Qwen? Video-LLaMA: Dormant. Qwen: 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 Video-LLaMA and Qwen? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Video-LLaMA: /tools/damo-nlp-sg-video-llama/trust; Qwen: /tools/qwenlm-qwen/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/_