This new AI edits any video! FREE & offline

This new AI edits any video! FREE & offline

by AI Search

Applied Sciences & Engineering AI — Models & Research UYQArtificial intelligence (AI)UYQFGenerative artificial intelligence
🎙 AI Search 👥 727K 📅 October 23, 2025 ⏱ 18 min 👁 100K 📄 tutorial 🧭 2026-09-07
Available in: English (current) Français

Keywords

DittoComfyUIvideo editingAIopen-source

Summary

The video introduces Ditto, a free and open-source AI model for editing videos using text prompts. It is based on Wan, another open-source video model by Ant Group. The creator demonstrates various capabilities: changing characters, adding objects, altering styles (e.g., to Pixar or Rick and Morty), and converting anime to realistic video (sim2real). The tutorial then provides a step-by-step guide to installing Ditto in ComfyUI, including downloading models (about 15 GB for the main model, plus others), setting up the workflow, and adjusting parameters like steps, CFG, and seed. The creator tests the global, style, and sim2real models, noting that the global model does not yet support local edits. The video also includes a sponsor segment for Epidemic Sound. The creator highlights the ease of use and the potential for high-quality results, while acknowledging limitations such as expression transfer and the need for a GPU with at least 11 GB VRAM.

151 words

Critical Evaluation

Value of the Information & Strength of the Argument

The video provides valuable, practical information for users interested in running AI video editing locally. The creator demonstrates the tool’s capabilities with clear examples and offers a detailed installation tutorial, which is highly useful for the target audience. The argumentation is straightforward and based on hands-on testing, which adds credibility. However, the video does not provide a critical analysis of the model’s limitations beyond a few observations, and the sponsor segment is clearly separated. The creator’s enthusiasm is evident, but the evaluation could be more balanced by discussing potential drawbacks more thoroughly.

Scientific Rigor, Source Quality, Title Accuracy

The video references the official GitHub repository for Ditto and other relevant tutorials. The sources are appropriate and directly related to the content. The title accurately reflects the content, as the video indeed presents a new AI tool for video editing that is free and offline. The creator also mentions the minimum VRAM requirement and provides links to additional resources. The video is well-structured with clear chapters, and the tutorial is easy to follow. However, the video does not cite any academic papers or external studies, which limits its scientific rigor. The sponsor segment is clearly marked and does not interfere with the tutorial’s integrity.

212 words

Title / Content Match

The title accurately reflects the content: the video presents a new AI tool for video editing that is free and offline, and demonstrates its use.

Quality & Reliability

7/10

The video provides a clear, step-by-step tutorial for installing and using an open-source AI video editing tool (Ditto) in ComfyUI. The creator demonstrates the tool's capabilities with multiple examples and explains technical settings. However, the video is primarily a tutorial and does not delve into rigorous scientific evaluation of the model's performance or limitations. The sponsor segment is clearly marked, and the creator acknowledges some limitations (e.g., expression transfer, local editing). Overall, the information is practical and reliable for its intended purpose, but not deeply scientific.

Chapters

Cited Sources

  • Ditto GitHub repository — Official repository for the Ditto AI video editing model, containing installation instructions and model downloads.
  • AI Search website — The creator's website for finding AI tools and jobs.
  • AI Search newsletter — The creator's weekly newsletter for AI news and updates.
  • Wan Animate tutorial — Tutorial on Wan Animate, a related tool for facial expression transfer.
  • ComfyUI tutorial — Tutorial on installing and using ComfyUI, the platform used for running Ditto.
  • VACE tutorial — Tutorial on VACE, another tool mentioned in the workflow.

Concurring Sources

  • Ditto GitHub repository — The official repository confirms the model's capabilities and installation instructions as shown in the video.

External References

Contribution & Novelties

The video provides a practical, step-by-step guide to installing and using Ditto, a newly released open-source AI video editing model. It demonstrates its capabilities and limitations through hands-on testing, which is valuable for users wanting to try it locally. The tutorial is clear and accessible, making it easier for non-experts to adopt the tool.

Pour aller plus loin :

  • Wan Video Model — Ditto is based on Wan, an open-source video generation model; understanding Wan helps contextualize Ditto’s capabilities.
  • ComfyUI — The platform used to run Ditto; learning ComfyUI is essential for using such models.
  • Diffusion Models — Ditto uses diffusion-based generation; this concept is fundamental to understanding how it works.

111 words

Radar Profile

The radar profile shows a balanced performance across all dimensions, with slightly higher scores in quantity of information and technical level, reflecting the tutorial's practical focus. The fiabilite_globale is moderate, indicating that while the information is useful, it lacks deep scientific rigor.

Reliability 7/10

💬 Positif : Sur les 30 commentaires analysés, la majorité exprime de l'enthousiasme et de l'intérêt pour l'outil, avec des remerciements pour le tutoriel et des questions sur les performances. Quelques commentaires notent des limitations, mais le climat général est très positif.