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Diffusion Bee vs Mochi Diffusion
Side-by-side comparison for macOS
Diffusion Bee
8.0Run Stable Diffusion locally
Mochi Diffusion
8.0Run Stable Diffusion natively
| Metric | Diffusion Bee | Mochi Diffusion |
|---|---|---|
| Category | Media & Design | Media & Design |
| AI Score | 8.0 | 8.0 |
| 30-day Installs | 195 | 40 |
| 90-day Installs | 706 | 126 |
| 365-day Installs | 2.2K | 402 |
| Version | 2.5.3 | 6.0 |
| Auto-updates | No | Yes |
| Deprecated | No | No |
| GitHub Stars | 13.5K | 7.9K |
| GitHub Forks | 716 | 362 |
| Open Issues | 397 | 8 |
| License | AGPL-3.0 | GPL-3.0 |
| Language | JavaScript | Swift |
| Last GitHub Commit | 1y ago | 2mo ago |
| First Seen | Oct 5, 2022 | Feb 13, 2023 |
Reviews
Diffusion Bee
Diffusion Bee simplifies running Stable Diffusion locally on M1 Macs with a one-click installer, making it accessible for artists, designers, and developers without technical expertise.
Runs Stable Diffusion locally on macOS with a graphical user interface.
Pros
- + Easy one-click installation process.
- + Optimized for M1 Mac performance.
- + No additional dependencies required.
Cons
- - No auto-update feature.
- - Black screen issues reported on Intel Macs.
Mochi Diffusion
Mochi Diffusion allows users to run Stable Diffusion natively on macOS, leveraging CoreML for optimized performance. It's ideal for artists and developers seeking a local AI image generation solution.
Runs Stable Diffusion natively on macOS using CoreML.
Pros
- + Native and optimized performance on macOS
- + Efficient use of CoreML for AI processing
- + Swift-based implementation for smooth operation
Cons
- - Limited support for certain Stable Diffusion models
- - Setup and configuration can be complex for some users