calcuis

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sd3.5-medium-gguf

like 8

did you fix the parameters? it involves random factors, even with the same prompt by default, i.e., if you draw a picture with more complicated elements (just like you draw a number from black box), then will take longer than normal process time; speed could be simply determined by file size by probability

did you fix the parameters? it involves random factors, even with the same prompt by default, i.e., if you dice a picture with more complicated elements, then will take longer than normal processing time; speed could be simply determined by file size by probability

I did not change any parameters except for U-net model loading, and fixed the seed. I tried several times and got the same result - Q8_0 is faster
Here is my computer configuration:
GPU - RTX2060 (6GB, overclocking)
CPU - i5 12400f
MEM - 16x2GB 3.2GHz
Also, I'm not sure what the phrase 'if you dice a picture with more complex elements' means. Does it mean' seed '? (Due to the translator)
I haven't tested other versions, but if Q5_K_M is faster on your computer, we may need more reports from people to draw conclusions.

which means random factor(s); dice probability; could try to generate few more times before jumping to the conclusion; model structure itself do affect the performance

which means random factor(s); dice probability; could try to generate few more times before jumping to the conclusion; model structure itself do affect the performance

Observation data:
Q8_0: 1.32s/it ~ 1.49s/it (median is 1.35s/it)
Q5_K_M: 1.68s/it ~ 2.83s/it (median 1.71s/it)

Q8_0 is 26.7% faster.

just a quick test with q4_0, q5_k_m and q8_0

then do it with q3_k_s and run q8_0 again

seems q8_0 is pretty much faster (disregard the memory buffer; fastest among them; with 4050); interesting

That's the answer.