Browse Models
The simplest way to self-host Meina Mix. Launch a dedicated cloud GPU server running Lab Station OS to download and serve the model using any compatible app or framework.
Download model weights for local inference. Must be used with a compatible app, notebook, or codebase. May run slowly, or not work at all, depending on your system resources, particularly GPU(s) and available VRAM.
MeinaMix is a Stable Diffusion checkpoint model optimized for artistic outputs with minimal prompting. The V12 version features improved image brightness and eye detail through block weighted merges. Works best with DPM++ samplers, CFG 4-9, and excels at both portrait and landscape generations with specific aspect ratios.
MeinaMix is a Stable Diffusion checkpoint model designed to generate high-quality anime-style artwork with minimal prompting requirements. Created by Meina, it exists within a broader family of models spanning versions V2 through V12, including specialized variants with and without VAE implementations and versions optimized for inpainting tasks.
The latest iteration, V12, introduces several notable improvements over its predecessors, particularly in image brightness control and high-resolution generation capabilities. Special attention has been paid to enhancing eye detail rendering, while simultaneously reducing prompt bias and random variations in outputs. However, this increased consistency means that some previously effective short prompts may require additional detail to achieve desired results.
While the exact training methodology and data sources remain undisclosed, the creator has mentioned utilizing block weighted merges with various settings in the development process. This technique appears to contribute to the model's ability to generate consistent, high-quality outputs across a range of prompt types.
For optimal results, users should consider the following recommended parameters:
The implementation of hires.fix is strongly recommended, particularly when generating images with characters at a distance. The recommended configuration includes using R-ESRGAN 4x+Anime6b with 10 steps at 0.3-0.6 denoising. For optimal results with K samplers, quantization is advised.
MeinaMix operates under the CreativeML Open RAIL-M license with specific addendums. The model and its variants are freely available, fostering an active community of users who share their creations and experiences. The license addendum provides detailed information about usage rights and restrictions.
Users can find support and share their experiences through the Meina Discord community, where they can discuss prompts, share images, and seek assistance with implementation challenges.