Comparison
stable-diffusion vs Video-LLaMA
Verdict
Pick stable-diffusion if stable-diffusion is a state-of-the-art latent text-to-image diffusion model underpinning image generation from textual inputs; pick Video-LLaMA if video-LLaMA is an audio-visual language model that enhances video and audio understanding capabilities for language models.
Markdown twin · stable-diffusion alternatives · Video-LLaMA alternatives
GraphCanon updated 3d
vs
Trust & integrity
| Signal | stable-diffusion | Video-LLaMA |
|---|---|---|
| Maintenance | Dormant (774d since push) As of 2w · github_public_v1 | Dormant (804d since push) As of 3d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization account As of 3d · 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
- stable-diffusion
- A latent text-to-image diffusion model
- Video-LLaMA
- Instruction-tuned Audio-Visual Language Model for Video Understanding
Stars
- stable-diffusion
- 73k
- Video-LLaMA
- 3.1k
Forks
- stable-diffusion
- 11k
- Video-LLaMA
- 287
Open issues
- stable-diffusion
- 616
- Video-LLaMA
- 69
Language
- stable-diffusion
- Jupyter Notebook
- Video-LLaMA
- Python
Adopt for
- stable-diffusion
- Stable-diffusion is a state-of-the-art latent text-to-image diffusion model underpinning image generation from textual inputs.
- Video-LLaMA
- Video-LLaMA is an audio-visual language model that enhances video and audio understanding capabilities for language models.
Persona
- stable-diffusion
- -
- Video-LLaMA
- -
Runtime
- stable-diffusion
- -
- Video-LLaMA
- -
License
- stable-diffusion
- Other
- Video-LLaMA
- BSD-3-Clause
Last pushed
- stable-diffusion
- Jun 18, 2024
- Video-LLaMA
- Jun 4, 2024
Categories
- stable-diffusion
- Computer Vision, Model Training
- Video-LLaMA
- Computer Vision, Model Training
Trust and health
Days since push
- stable-diffusion
- 774d
- Video-LLaMA
- 804d
Open issues (now)
- stable-diffusion
- 616
- Video-LLaMA
- 69
Stars delta
- stable-diffusion
- Unknown
- Video-LLaMA
- +2 (30d)
Open issues delta
- stable-diffusion
- Unknown
- Video-LLaMA
- -1 (30d)
Full report
- stable-diffusion
- Trust report
- Video-LLaMA
- Trust report
Choose stable-diffusion if…
- stable-diffusion is primarily Jupyter Notebook; Video-LLaMA is Python.
- License: stable-diffusion is Other, Video-LLaMA is BSD-3-Clause.
- Tags unique to stable-diffusion: diffusion-model, latent space, text-to-image.
- For generating images based on text prompts with high fidelity and artistic detail.
When NOT to use stable-diffusion
- If the computational resources are limited, as it requires significant GPU power to train or fine-tune models.
- In cases where real-time generation performance is critical, due to its computation-intensive process.
Choose Video-LLaMA if…
- Video-LLaMA is primarily Python; stable-diffusion is Jupyter Notebook.
- License: Video-LLaMA is BSD-3-Clause, stable-diffusion 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 (CompVis/stable-diffusion) · observed Aug 1, 2026
- GitHub forks (CompVis/stable-diffusion) · observed Aug 1, 2026
- Last push (CompVis/stable-diffusion) · observed Jun 18, 2024
- License file (Other) · observed Aug 1, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (DAMO-NLP-SG/Video-LLaMA) · observed Aug 18, 2026
- GitHub forks (DAMO-NLP-SG/Video-LLaMA) · observed Aug 18, 2026
- Last push (DAMO-NLP-SG/Video-LLaMA) · observed Jun 4, 2024
- License file (BSD-3-Clause) · observed Aug 18, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: stable-diffusion 73k · Video-LLaMA 3.1k (synced Aug 1, 2026).
Common questions
- What is the difference between stable-diffusion and Video-LLaMA?
- stable-diffusion: A latent text-to-image diffusion model. 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 stable-diffusion over Video-LLaMA?
- Choose stable-diffusion over Video-LLaMA when stable-diffusion is primarily Jupyter Notebook; Video-LLaMA is Python; License: stable-diffusion is Other, Video-LLaMA is BSD-3-Clause; Tags unique to stable-diffusion: diffusion-model, latent space, text-to-image; For generating images based on text prompts with high fidelity and artistic detail.
- When should I choose Video-LLaMA over stable-diffusion?
- Choose Video-LLaMA over stable-diffusion when Video-LLaMA is primarily Python; stable-diffusion is Jupyter Notebook; License: Video-LLaMA is BSD-3-Clause, stable-diffusion 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 stable-diffusion?
- If the computational resources are limited, as it requires significant GPU power to train or fine-tune models. In cases where real-time generation performance is critical, due to its computation-intensive process.
- 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 stable-diffusion or Video-LLaMA more popular on GitHub?
- stable-diffusion has more GitHub stars (73,254 vs 3,141). Stars measure visibility, not whether either tool fits your constraints.
- Are stable-diffusion and Video-LLaMA open source?
- Yes - both are open-source projects on GitHub (stable-diffusion: Other, Video-LLaMA: BSD-3-Clause).
- Where can I find alternatives to stable-diffusion or Video-LLaMA?
- GraphCanon lists graph-backed alternatives at stable-diffusion alternatives and Video-LLaMA alternatives (stable-diffusion 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, stable-diffusion or Video-LLaMA?
- stable-diffusion: 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 stable-diffusion and Video-LLaMA?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: stable-diffusion trust report; Video-LLaMA trust report.