Quantization of Kroma v0.3 Turbo by Lodestones primarily meant for low VRAM/RAM usage, expect degradation in quality compared to INT8 Convrot only quants or BF16, saves ~64.3% in storage relative to BF16. <hr />Spent a great deal of time working on which layers to quantize to what method (INT8 Convrot or W4A4 Convrot) and I kind of like this one.<span style="background-color:rgb(26, 27, 30);color:rgb(193, 194, 197);font-family:-apple-system, BlinkMacSystemFont, &quot;Segoe UI&quot;, Roboto, Helvetica, Arial, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;;font-size:16px">Used a simple T2I workflow, no second stage or upscaling done as I'm too lazy for that.Tested on:<ul><li>NVIDIA GTX 1660 Super 6 GB</li><li>32 GB System RAM</li></ul>Test settings:<ul><li>8 steps</li><li>CFG 1</li><li>Euler / Simple</li><li>696 × 1048 resolution (0.7 on resolution selector)</li><li>Approximately 9 s/it on a GTX 1660 Super</li></ul>

Files with SHA256: 592dd53d619d9aaf8cf3038d5f917f58f48143385b45a995e1b3a882547f9304