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This is one of the "smartest" models you can fit on a 24GB GPU now, with no offloading and very little quantization loss. It feels big and insightful, like a better (albeit dry) Llama 3.3 70B with thinking, and with more STEM world knowledge than QwQ 32B, but comfortably fits thanks the new exl3 quantization!
You need to use a backend that support exl3, like (at the moment) text-gen-web-ui or (soon) TabbyAPI.
^ what was said, not supported yet, though you can give it a shot theoretically.
Basically exl3 means you can run 32B models, totally on GPU without a ton of quantization loss, if you can get it working on your computer. But exl2/exl3 is less popular largely because it’s PyTorch based, hence more finicky to setup (no GGUF single files, no Macs, no easy install, especially on AMD).