Mistral Small 22B just dropped today and I am blown away by how good it is. I was already impressed with Mistral NeMo 12B’s abilities, so I didn’t know how much better a 22B could be. It passes really tough obscure trivia that NeMo couldn’t, and its reasoning abilities are even more refined.
With Mistral Small I have finally reached the plateu of what my hardware can handle for my personal usecase. I need my AI to be able to at least generate around my base reading speed. The lowest I can tolerate is 1.5~T/s lower than that is unacceptable. I really doubted that a 22B could even run on my measly Nvidia GTX 1070 8G VRRAM card and 16GB DDR4 RAM. Nemo ran at about 5.5t/s on this system, so how would Small do?
Mistral Small Q4_KM runs at 2.5T/s with 28 layers offloaded onto VRAM. As context increases that number goes to 1.7T/s. It is absolutely usable for real time conversation needs. I would like the token speed to be faster sure, and have considered going with the lowest Q4 recommended to help balance the speed a little. However, I am very happy just to have it running and actually usable in real time. Its crazy to me that such a seemingly advanced model fits on my modest hardware.
Im a little sad now though, since this is as far as I think I can go in the AI self hosting frontier without investing in a beefier card. Do I need a bigger smarter model than Mistral Small 22B? No. Hell, NeMo was serving me just fine. But now I want to know just how smart the biggest models get. I caught the AI Acquisition Syndrome!
Good! Try the IQM, XS, and XSS quantizations as well, especially if you try a 14B, as they “squeeze” the model into less space better than the Q3_K quantizations.
Yeah I’m liking the 32B as well. If you are looking for speed just for ultilitarian Q/A, you might want to keep a Deepseek Lite V2 Code GGUF on hand, as it’s uber fast partially offloaded.