Comparison
caffe vs Video-LLaMA
Verdict
Pick caffe if caffe is designed for deep learning tasks, especially those involving computer vision, and is written in C++ to ensure efficiency; pick Video-LLaMA if video-LLaMA is an audio-visual language model that enhances video and audio understanding capabilities for language models.
Markdown twin · caffe alternatives · Video-LLaMA alternatives
GraphCanon updated 2w
Trust & integrity
| Signal | caffe | Video-LLaMA |
|---|---|---|
| Maintenance | Dormant (732d since push) As of 2w · github_public_v1 | Dormant (774d since push) As of 1mo · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization account As of 1mo · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- caffe
- Caffe is a fast open framework for deep learning.
- Video-LLaMA
- Instruction-tuned Audio-Visual Language Model for Video Understanding
Stars
- caffe
- 35k
- Video-LLaMA
- 3.1k
Forks
- caffe
- 18k
- Video-LLaMA
- 288
Open issues
- caffe
- 1.5k
- Video-LLaMA
- 70
Language
- caffe
- C++
- Video-LLaMA
- Python
Adopt for
- caffe
- Caffe is designed for deep learning tasks, especially those involving computer vision, and is written in C++ to ensure efficiency.
- Video-LLaMA
- Video-LLaMA is an audio-visual language model that enhances video and audio understanding capabilities for language models.
Persona
- caffe
- -
- Video-LLaMA
- -
Runtime
- caffe
- -
- Video-LLaMA
- -
License
- caffe
- Caffe is available under the BSD 2-Clause license.
- Video-LLaMA
- BSD-3-Clause
Last pushed
- caffe
- Jul 31, 2024
- Video-LLaMA
- Jun 4, 2024
Categories
- caffe
- Computer Vision, Model Training
- Video-LLaMA
- Computer Vision, Model Training
Trust and health
Days since push
- caffe
- 732d
- Video-LLaMA
- 774d
Open issues (now)
- caffe
- 1.5k
- Video-LLaMA
- 70
Full report
- caffe
- Trust report
- Video-LLaMA
- Trust report
Choose caffe if…
- caffe is primarily C++; Video-LLaMA is Python.
- License: caffe is Other, Video-LLaMA is BSD-3-Clause.
- Pricing: Free to use under open source licensing with no monetary charges..
- Tags unique to caffe: deep-learning, machine-learning, vision.
- - You need a framework that supports high-performance convolutional networks particularly suited for image classification
When NOT to use caffe
- - Your primary task involves natural language processing rather than computer vision challenges, where specialized frameworks might outperform Caffe
- - You seek a framework that integrates seamlessly with Python for both training and inference, as Caffe relies heavily on C++ for its core operations
Choose Video-LLaMA if…
- Video-LLaMA is primarily Python; caffe is C++.
- License: Video-LLaMA is BSD-3-Clause, caffe is Other.
- 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..
- Tags unique to Video-LLaMA: blip2, cross-modal-pretraining, large language models, llama.
- 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 NOT to use 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (BVLC/caffe) · observed Aug 3, 2026
- GitHub forks (BVLC/caffe) · observed Aug 3, 2026
- Last push (BVLC/caffe) · observed Jul 31, 2024
- License file (Other) · observed Aug 3, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (DAMO-NLP-SG/Video-LLaMA) · observed Jul 18, 2026
- GitHub forks (DAMO-NLP-SG/Video-LLaMA) · observed Jul 18, 2026
- Last push (DAMO-NLP-SG/Video-LLaMA) · observed Jun 4, 2024
- License file (BSD-3-Clause) · observed Jul 18, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: caffe 35k · Video-LLaMA 3.1k (synced Aug 3, 2026).
Common questions
- What is the difference between caffe and Video-LLaMA?
- caffe: Caffe is a fast open framework for deep learning.. Video-LLaMA: Instruction-tuned Audio-Visual Language Model for Video Understanding. See the comparison table for live GitHub stats and shared categories.
- When should I choose caffe over Video-LLaMA?
- Choose caffe over Video-LLaMA when caffe is primarily C++; Video-LLaMA is Python; License: caffe is Other, Video-LLaMA is BSD-3-Clause; Pricing: Free to use under open source licensing with no monetary charges.; Tags unique to caffe: deep-learning, machine-learning, vision; - You need a framework that supports high-performance convolutional networks particularly suited for image classification.
- When should I choose Video-LLaMA over caffe?
- Choose Video-LLaMA over caffe when Video-LLaMA is primarily Python; caffe is C++; License: Video-LLaMA is BSD-3-Clause, caffe is Other; 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.; Tags unique to Video-LLaMA: blip2, cross-modal-pretraining, large language models, llama; 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 avoid caffe?
- - Your primary task involves natural language processing rather than computer vision challenges, where specialized frameworks might outperform Caffe - You seek a framework that integrates seamlessly with Python for both training and inference, as Caffe relies heavily on C++ for its core operations
- 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.
- Is caffe or Video-LLaMA more popular on GitHub?
- caffe has more GitHub stars (34,573 vs 3,139). Stars measure visibility, not whether either tool fits your constraints.
- Are caffe and Video-LLaMA open source?
- Yes - both are open-source projects on GitHub (caffe: Other, Video-LLaMA: BSD-3-Clause).
- Where can I find alternatives to caffe or Video-LLaMA?
- GraphCanon lists graph-backed alternatives at caffe alternatives and Video-LLaMA alternatives (caffe markdown twin, Video-LLaMA 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, caffe or Video-LLaMA?
- caffe: Dormant. Video-LLaMA: Dormant. 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 caffe and Video-LLaMA?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: caffe trust report; Video-LLaMA trust report.