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Head to head, on real hardware.

One head-to-head test case, run on the same workstation: a 46.8M-cell FDTD mesh stepped 5,000 times. RayRF on GPU, RayRF on CPU, and openEMS all solve the identical setup. Bars show FDTD cell updates per second. Longer is faster.

Looking for measured-vs-simulated S-parameter comparisons? Those live on the Validation page.

Cell updates per second, longer is faster
46.8M cells, 5,000 timesteps
RayRF GPU
RTX 5070 Ti, CUDA
9,843 MCell/s - 68.5x FASTER
25.4 s
wall-clock
RayRF CPU
Ryzen 9 9950X, OpenMP, 32 threads
623 MCell/s - 4.3x FASTER
6 m 17 s
wall-clock
openEMS
Ryzen 9 9950X, CPU SSE, 32 threads (baseline)
144 MCell/s - 1.0x BASELINE
27 m 44 s
wall-clock

Setup detail

The two engines build their meshes independently, so the active cell counts differ by 0.46% (212,321 cells) on the same geometry. openEMS actually has fewer cells than RayRF here, so if anything the comparison runs slightly against RayRF, which is updating more cells per timestep. Throughput is computed against each engine's own cell count, so the per-engine MCell/s numbers are directly comparable.

RayRF (GPU / CPU)
openEMS
Cells in active mesh
46,815,696
46,603,375
Timesteps
5,000
5,000
Total wall-clock
25.35 s / 6 m 17 s
27 m 44 s

Hardware: AMD Ryzen 9 9950X, NVIDIA RTX 5070 Ti, 32 GB RAM, Windows 11 (CUDA driver from NVIDIA Studio 580.xx series). Software: RayRF v1.0.0, openEMS 0.0.36 (CPU SSE build). Test case: 5.8 GHz rectangular patch reference, 5x mesh scale, 5,000 timesteps. Run 2026-05-08.

Built for PCB RF simulation.

Faster results at a fraction of the cost. Validated against measurements, with a live editor.

RayRF
openEMS
CST / HFSS
Price
$29-199/mo
Free
$10K-50K/yr
Live edit to results
~1 s
batch only
batch only
Reference benchmark
25 s
27 m 44 s
N/A*
Full GUI editor
Yes
partial
Yes
VNA-validated refs
Measured suite
none
none
Buy online today
Yes
n/a
contact sales

* CST/HFSS not benchmarked as they do not permit public comparisons of their software. Ironic.

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