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[Trevor Baker]

Great topic, and I want to push back a bit on the framing in #1—the physics step and network tickrate are related but genuinely decoupled systems, and conflating them is where a lot of these benchmarks go wrong. In a fixed-timestep integration scheme (which most competitive engines use for determinism), the simulation advances in discrete fixed increments—say 1/64s or 1/128s—regardless of your render framerate or the server’s actual network tick. The accumulator pattern batches elapsed time into those fixed steps, and if a frame takes too long, it runs multiple physics steps in one render pass to catch up. So on paper you can be running 240 FPS while physics still simulates at the server’s 128 Hz. The real problem shows up when people benchmark “input latency” without separating the render pipeline latency from the simulation latency

"Note: Statements are my personal gaming experience; not official hardware support."

[Trevor Baker]

The single biggest mistake I see teams make when building replay systems is treating save-state serialization and replay as two separate problems when they’re really the same one. If you’re capturing full heap snapshots and deserializing them back, you’re almost guaranteed non-deterministic behavior because pointer addresses, hash table iteration order, and memory allocation patterns shift between runs. The clean architecture is deterministic lockstep: the simulation is a pure function of the input stream plus initial seed, and you serialize inputs rather than state. That’s why fighting games and RTS titles replay as compressed input logs rather than frame-by-frame snapshots.

The catch you have to solve before anything else is floating-point determinism—sqrt, trig?

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