--- title: "custom-diffusion vs ai-engineering-from-scratch" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/adobe-research-custom-diffusion-vs-rohitg00-ai-engineering-from-scratch" tools: ["adobe-research-custom-diffusion", "rohitg00-ai-engineering-from-scratch"] --- # custom-diffusion vs ai-engineering-from-scratch *GraphCanon updated Jul 11, 2026* ## Verdict Pick custom-diffusion when license: custom-diffusion is Other, ai-engineering-from-scratch is MIT; pick ai-engineering-from-scratch when license: ai-engineering-from-scratch is MIT, custom-diffusion is Other. [custom-diffusion](https://www.cs.cmu.edu/~custom-diffusion) reports 2.0k GitHub stars, 141 forks, and 52 open issues, last pushed May 24, 2026. [ai-engineering-from-scratch](https://aiengineeringfromscratch.com) has 38k stars, 6.3k forks, and 96 open issues, last pushed Jun 25, 2026. Figures are from public GitHub metadata via [custom-diffusion's repository](https://github.com/adobe-research/custom-diffusion) and [ai-engineering-from-scratch's repository](https://github.com/rohitg00/ai-engineering-from-scratch). | | [custom-diffusion](/tools/adobe-research-custom-diffusion.md) | [ai-engineering-from-scratch](/tools/rohitg00-ai-engineering-from-scratch.md) | | --- | --- | --- | | Tagline | Custom Diffusion: Multi-Concept Customization of Text-to-Image Diffusion (CVPR 2023) | Learn it. Build it. Ship it for others. | | Stars | 1,975 | 37,922 | | Forks | 141 | 6,329 | | Open issues | 52 | 96 | | Language | Python | Python | | Adopt for | - | Specifically designed for individuals looking to build a comprehensive understanding of AI tools and frameworks from the ground up. | | Persona | - | - | | Runtime | - | - | | License | Other | MIT | | Categories | Model Training, Computer Vision | LLM Frameworks, AI Agents, Computer Vision, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [custom-diffusion](/tools/adobe-research-custom-diffusion.md) | [ai-engineering-from-scratch](/tools/rohitg00-ai-engineering-from-scratch.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Active (82%) | | Days since push | 47d | 15d | | Open issues (now) | 52 | 96 | | Owner type | Organization | User | | Security scan | No lockfile | No MCP manifest | | Full report | [trust report](/tools/adobe-research-custom-diffusion/trust.md) | [trust report](/tools/rohitg00-ai-engineering-from-scratch/trust.md) | ## Decision facts: ai-engineering-from-scratch - **Pricing:** freemium - The `ai-engineering-from-scratch` repository is free and open-source under an MIT license, but for full access to additional resources or support, a paid option may be provided. Consult official or up - **Adopt for:** Specifically designed for individuals looking to build a comprehensive understanding of AI tools and frameworks from the ground up. ## Choose when ### Choose custom-diffusion if… - License: custom-diffusion is Other, ai-engineering-from-scratch is MIT. - Tags unique to custom-diffusion: text-to-image-generation, customization, fine-tuning, few-shot. - Also covers Model Training. ### Choose ai-engineering-from-scratch if… - License: ai-engineering-from-scratch is MIT, custom-diffusion is Other. - Pricing: The `ai-engineering-from-scratch` repository is free and open-source under an MIT license, but for full access to additional resources or support, a paid option may be provided. Consult official or up. - Tags unique to ai-engineering-from-scratch: deep-learning, ai-engineering, agents, llm. - Also covers LLM Frameworks, AI Agents, Developer Tools. - When you want to start with foundational knowledge and learn the intricacies behind AI systems. ## When NOT to use custom-diffusion - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ## When NOT to use ai-engineering-from-scratch - If you are looking for a quick setup or ready-to-go solution without diving into the foundational understanding. - When your project requires immediate practical application with less emphasis on self-implemented solutions from scratch. ## Common questions ### What is the difference between custom-diffusion and ai-engineering-from-scratch? custom-diffusion: Custom Diffusion: Multi-Concept Customization of Text-to-Image Diffusion (CVPR 2023). ai-engineering-from-scratch: Learn it. Build it. Ship it for others.. See the comparison table for live GitHub stats and shared categories. ### When should I choose custom-diffusion over ai-engineering-from-scratch? Choose custom-diffusion over ai-engineering-from-scratch when License: custom-diffusion is Other, ai-engineering-from-scratch is MIT; Tags unique to custom-diffusion: text-to-image-generation, customization, fine-tuning, few-shot; Also covers Model Training. ### When should I choose ai-engineering-from-scratch over custom-diffusion? Choose ai-engineering-from-scratch over custom-diffusion when License: ai-engineering-from-scratch is MIT, custom-diffusion is Other; Pricing: The `ai-engineering-from-scratch` repository is free and open-source under an MIT license, but for full access to additional resources or support, a paid option may be provided. Consult official or up; Tags unique to ai-engineering-from-scratch: deep-learning, ai-engineering, agents, llm; Also covers LLM Frameworks, AI Agents, Developer Tools; When you want to start with foundational knowledge and learn the intricacies behind AI systems. ### When should I avoid custom-diffusion? Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ### When should I avoid ai-engineering-from-scratch? If you are looking for a quick setup or ready-to-go solution without diving into the foundational understanding. When your project requires immediate practical application with less emphasis on self-implemented solutions from scratch. ### Is custom-diffusion or ai-engineering-from-scratch more popular on GitHub? ai-engineering-from-scratch has more GitHub stars (37,922 vs 1,975). Stars measure visibility, not whether either tool fits your constraints. ### Are custom-diffusion and ai-engineering-from-scratch open source? Yes - both are open-source projects on GitHub (custom-diffusion: Other, ai-engineering-from-scratch: MIT). ### Where can I find alternatives to custom-diffusion or ai-engineering-from-scratch? GraphCanon lists graph-backed alternatives at [custom-diffusion alternatives](/tools/adobe-research-custom-diffusion/alternatives) and [ai-engineering-from-scratch alternatives](/tools/rohitg00-ai-engineering-from-scratch/alternatives) ([custom-diffusion markdown twin](/tools/adobe-research-custom-diffusion/alternatives.md), [ai-engineering-from-scratch markdown twin](/tools/rohitg00-ai-engineering-from-scratch/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 [this comparison](/compare/adobe-research-custom-diffusion-vs-rohitg00-ai-engineering-from-scratch.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, custom-diffusion or ai-engineering-from-scratch? custom-diffusion: Steady. ai-engineering-from-scratch: 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 custom-diffusion and ai-engineering-from-scratch? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [custom-diffusion trust report](/tools/adobe-research-custom-diffusion/trust); [ai-engineering-from-scratch trust report](/tools/rohitg00-ai-engineering-from-scratch/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=adobe-research-custom-diffusion`](/api/graphcanon/graph?tool=adobe-research-custom-diffusion) - 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/_