Tickrate Scaling and Physics Simulation Step Decoupling: Competitive Benchmark Analysis and Залізо Interactions

[Sam King]

I’ve been running benchmark runs across tickrate scaling and physics step decoupling, comparing a fixed 128-tick server against variable-timestep client physics with interpolation. My main question is where the actual bottleneck shifts — when you decouple the physics tick from the render frame, does the engine’s fixed-step loop start bottlenecking on a single core, or does the extra CPU overhead get absorbed by better multi-threading?

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[Austin Turner]

Great topic to dig into. The core thing most people miss is that tickrate and physics timestep are two separate simulation clocks, and decoupling them properly is what actually separates a server that “feels solid” from one that feels floaty. In engines using a fixed-timestep accumulator pattern (which is what you want for competitive integrity), the physics step runs at a constant frequency—say 64Hz or 128Hz—regardless of where your render frame rate lands. This means input sampling, interpolation, and hitbox queries all resolve against the same deterministic simulation state, so a 128-tick server processes player movement 2x more granularly than a 64-tick one, and your hit registration aligns closer to actual server-side position rather than your local prediction. The danger zone is when the render loop and simulation start contending: if your game ties physics to

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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

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[Ethan Rivera]

Decoupling the physics step from the render loop is genuinely where most people misunderstand the problem, so let me be clear about the mechanism. The correct pattern is a fixed-timestep accumulator (think Fiedler’s “Fix Your Timestep” approach): you advance simulation at a constant delta—say 1/128s for a 128-tick server or 6.5ms for 60-tick netcode—while rendering runs at whatever FPS the GPU can produce. The accumulator grabs leftover time each frame and runs zero, one, or multiple fixed updates, then interpolates the render between the last two authoritative states. The danger appears when people try to “sync” physics to frame time by scaling the timestep to FPS; that introduces frame-dependent simulation variance, and on low, jittery frametimes you get variable substep counts that change collision resolution and hitbox behavior between frames. For competitive play this matters because tunneling (fast projectiles or bullets skipping past cover

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