NVIDIA · 80 GB HBM2e · 2039 GB/s bandwidth ·
Alibaba · 72.7B · model ctx up to 128K
Yes — the A100 80GB SXM4 (80 GB HBM2e) can run Qwen2.5-72B-Instruct. At Q4 with the default 8K context it needs ≈ 55.53 GB VRAM (weights 39.99 GB + KV cache 14.54 GB + 1 GB runtime overhead), which fits within 80 GB. Decode at Q4/8K: ≈ 16.47 tok/s (measured, batch 1). FP16 needs ≈ 160.94 GB — does not fit on this card. Estimates come from memory-bandwidth math; rows tagged measured override estimates. Relative ranking is more reliable than absolute tok/s. Methodology.
Fit & speed by quant and context
Quant
Context
VRAM needed
Fits?
tok/s (decode)
Q4
4K
48.26 GB
Yes
16.47measured
Q4
8K default
55.53 GB
Yes
16.47measured
Q4
32K
99.15 GB
No
16.47measured
FP16
4K
153.67 GB
No
3.8est.
FP16
8K default
160.94 GB
No
3.5est.
FP16
32K
204.56 GB
No
2.1est.
Fits = weights + KV(ctx) + 1 GB overhead ≤ 95% of VRAM. Measured
anchors are context-agnostic; the fit verdict is recomputed per context. A missing tok/s
means the model is far beyond this card (offload-only territory).