Short answer: yes, on a 2× H100 NVL (188GB) at FP16/BF16. Long answer below.
Qwen 2.5 72B has 72.7B parameters. At FP16 that's 145 GB of raw weights. Quantization shrinks that, but you also need budget for the KV cache (definition), framework overhead, and safety headroom. The rule of thumb: real usable budget on a card is roughly its nameplate VRAM minus 25%. That's how the table below was computed.
Smallest GPU that fits Qwen 2.5 72B at any quant: 2× H100 NVL at FP16/BF16.
Lossless inference needs 145 GB. Pick from 5 cards.
None of the showcase quants fit on a 24GB card. Step up.
Open the calculator pre-tuned for Qwen 2.5 72B: ↗ /calc?model=qwen-2-5-72b
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