Video-LLaMA vs LlamaFactory

Common questions

What is the difference between Video-LLaMA and LlamaFactory?

Video-LLaMA: Instruction-tuned Audio-Visual Language Model for Video Understanding. LlamaFactory: Unified Efficient Fine-Tuning of 100+ LLMs & VLMs. 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; Requirements: Ensure access to compatible hardware for video and audio processing tasks.; Consider the availability of Chinese text representation as a potential advantage or limitation based on your project needs.; LlamaFactory focuses on efficient fine-tuning of various LLMs and VLMs, which is an alternative approach to creating instruction-tuned models like Video-LLaMA that aim at audio-visual understanding; Tags unique to Video-LLaMA: blip2, cross-modal-pretraining, minigpt4, multi-modal-chatgpt; Also covers Computer Vision; When you need to process video content with instruction-tuned multimodal capabilities, especially when working with videos that require both visual and auditory analysis.

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; Requirements: Min 4 GB RAM; Requires Docker; Hardware requirements vary based on the method and model size. For example, full fine-tuning of a 7B model requires 120GB of memory, while QLoRA with 2-bit can ; Installation is mandatory and can be done from source or via Docker. Additional dependencies like metrics and deepspeed are optional.; For Windows users, manual installation of PyTorch with CUDA support is required, and bitsandbytes must be installed for QLoRA support.; LlamaFactory focuses on efficient fine-tuning of various LLMs and VLMs, which is an alternative approach to creating instruction-tuned models like Video-LLaMA that aim at audio-visual understanding; Tags unique to LlamaFactory: agent, ai, deepseek, fine-tuning; Also covers LLM Frameworks; Use LlamaFactory when you need to fine-tune a wide range of large language models and vision-language models with methods like LoRA, QLoRA, and quantization.

When should I avoid Video-LLaMA?

Do not use when the primary focus is on languages other than English and Chinese, as the model's representation capabilities outside these languages might be limited. Avoid using Video-LLaMA if you require real-time audio processing in a deployment environment that does not support Vicuna-7B audio branch currently running on A10-24G GPUs.

When should I avoid LlamaFactory?

Avoid LlamaFactory if you are working with models not included in its supported list of over 100 models, as it may not provide the necessary fine-tuning capabilities. Do not use LlamaFactory if you are working in an environment where Python or specific dependencies like PyTorch and bitsandbytes cannot be installed or are not supported. LlamaFactory may not be suitable if you require real-time or near-real-time fine-tuning capabilities, as the setup and installation process can be complex and time-consuming.

Is Video-LLaMA or LlamaFactory more popular on GitHub?

LlamaFactory has more GitHub stars (74,849 vs 3,141). 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 Video-LLaMA alternatives and LlamaFactory alternatives (Video-LLaMA markdown twin, LlamaFactory markdown twin), 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 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 trust report; LlamaFactory trust report.