Unit Conversions That Ship

80 GB on the box. 81,920 MiB in nvidia-smi. Vendors label VRAM in binary, so what goes missing before your first tensor is overhead — not units.

Four converters. No fluff. Each one catches a gap between what vendors print and what your systems actually report. VRAM marketing vs CUDA reality. Network line rate vs storage benchmark units. GPU cluster TFLOPS vs datacenter PFLOPS. Sustained throughput vs daily transfer volume. The math is simple — the consequences of getting it wrong aren't.

VRAM GB →GiB / MiB

A100 80 GB. nvidia-smi reports 81,920 MiB, not 74.5 GiB — GPU labels are binary, so the storage conversion runs the wrong way. ECC rows, CUDA context and library workspace eat the rest.

GB-to-GiB Converter →

TFLOPS →PFLOPS

8× H100 nodes = 15.8 PFLOPS FP8. Your architecture review deck still says TFLOPS. Convert before the VP asks why the number looks small.

TFLOPS →PFLOPS Scaler →

Mbps →MB/s Throughput

ISP quotes 1,000 Mbps. Your NVMe array benchmarks in MB/s. Divide by 8. Subtract 5—2% for protocol overhead. Now size the pipe.

Mbps →MB/s Converter →

Gbps →TB / Day Egress

10 Gbps sustained = 108 TB/day. At AWS egress rates that's $9,180/day. Model the pipe before the CFO forwards you the bill with a question mark.

Gbps →TB/day Egress Meter →

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