The Tool Desk
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What the published numbers do—and do not—show
A 2015 study by Simon Fraser University researchers measured a computer running the Heaven graphics benchmark at about 158 W at the wall. Starting OBS x264 recording at 30 FPS raised the system draw by about 100 W, to around 250 W. This is a specific result for that machine and combined workload. It is not a typical estimate for a loop stream, a modern PC, or YouTube streaming.
The researchers’ 60 FPS run used slightly less total power than their 30 FPS run. CPU encoding interfered with the benchmark and reduced GPU utilization, illustrating why utilization percentages or settings alone cannot predict whole-system electricity use. The study did not test a matched YouTube loop-stream workload.
Other published work does not supply a universal substitute. A 2024 paper on HEVC software encoding reported a 5.36% mean absolute percentage error averaged over presets for its energy-estimation model. That is the model’s performance within the paper, not a wattage estimate or expected error range for your streaming setup. A 2024 survey also identifies factors such as encoding, network equipment, storage, retrieval, decoding, and displays, and notes the lack of a comprehensive open measurement dataset spanning devices and coding parameters.
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What changes the extra draw
- Computer and baseline workload: A low-power PC at idle and a gaming PC rendering a scene have different starting points. If the stream also captures or composites a demanding game, the total may include substantial work beyond encoding.
- Encoder and preset: OBS says x264 presets trade CPU use against image quality. A slower software preset may change the workload; test the actual preset you plan to use.
- Resolution and frame rate: Both affect rendering and encoding workload. Compare identical output settings rather than inferring a cost from resolution or FPS alone.
- Scene and competing activity: Overlays, sources, capture, other GPU tasks, and background applications can affect the result.
- Measurement boundary: A wall reading for the whole PC is not an isolated measurement of the encoder. Including a monitor or other peripherals changes the total, so keep the boundary consistent.
Software x264 versus hardware encoding
Software x264 uses the CPU for encoding. Hardware encoding shifts encoding work to a specialized component in a supported GPU. OBS generally recommends hardware encoding for performance because it takes work off the CPU, but that does not guarantee lower total system watts or identical image quality. OBS also cautions that some earlier hardware encoders could produce lower quality at the same bitrate than software x264 using its default veryfast preset.
For a useful comparison, run both options on your own computer with the same loop, scene, resolution, frame rate, bitrate, duration, network setup, and background applications. Compare average whole-system wall watts, resulting energy, visual quality at the bitrate you can use, and stream stability. A wattage advantage is not useful if the resulting picture or stream behavior is unacceptable.
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How to measure your streaming PC’s added electricity
- Measure at the wall. Use a plug-in energy meter or another suitable whole-system power measurement at the computer’s wall connection. Keep the monitor and unrelated equipment off the measured circuit if you want the computer’s draw; if they must be included, leave them included for every run. A whole-system meter will not isolate the encoder chip.
- Set up matched runs. Use the same machine, loop file, scene, audio, output resolution, frame rate, bitrate, duration, network setup, and background applications. Measure a baseline and then a software-encoding stream. If available, make a third run with hardware encoding.
- Allow readings to stabilize and repeat. Record average watts across a stable interval, not a momentary peak. Repeat runs to reduce noise, and use the same measurement interval for each condition.
- Subtract the matched baseline. Incremental watts = average watts during the software-encoding run minus average watts during the baseline. If the baseline already includes the same looping and scene work without software encoding, the difference is more informative than comparing against an unrelated idle reading.
- Convert the difference to energy. Incremental kWh = incremental watts × stream hours ÷ 1,000. For example, if your measured difference were 40 W over 24 hours, the added energy would be 0.96 kWh. This is an arithmetic example, not a reported result for a YouTube stream.
- Document what you tested. Record the PC, encoder and preset, resolution, frame rate, bitrate, duration, scene complexity, and what the meter included. Without these details, a wattage figure is easy to misapply.
YouTube’s encoding is separate from your PC’s electricity
YouTube accepts live streams from streaming software or a hardware encoder and transcodes them on its platform into formats for viewers. That server-side transcoding is separate from the electricity used by the creator’s computer. YouTube’s cited documentation does not publish a per-stream electricity figure, so it should not be added to a PC wall-meter reading or presented as a known creator-side wattage.
Common measurement mistakes
- Using the 100 W study result as a typical loop-stream estimate: It came from one 2015 system recording with OBS while a graphics benchmark was running. Measure the actual loop workload instead.
- Comparing different scenes or settings: A different resolution, FPS, bitrate, scene, or background task can change the workload. Keep the runs matched.
- Relying on CPU or GPU utilization alone: Utilization is not a wall-power measurement, and one component’s workload can change another’s. Measure average system watts.
- Mixing measurement boundaries: Adding or removing a monitor, speakers, or other equipment between runs undermines the subtraction. Keep the meter boundary fixed.
- Treating a short peak as continuous draw: Use a stable average over a representative interval; multiply the measured incremental watts by hours only when estimating energy for comparable conditions.
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