For OBS versus FFmpeg electricity use on a 24/7 YouTube PC, neither programme is the automatic winner. The lower-energy setup is the one that uses less cumulative energy on your own machine during a fair, matched stream test, measured at the wall rather than guessed from CPU or GPU utilisation.
Keep the PC, video, output settings and measurement interval the same, then compare the meter readings. That tells you what your particular setup uses; it does not establish a result for every computer, encoder or looping video.
Why the software name is not enough
OBS and FFmpeg are not fixed workloads. OBS can decode a source, composite it with other scene elements, apply filters and encode the output. FFmpeg can be configured with different decoding, filtering and encoding paths. A comparison between their names alone leaves too many variables unspecified to explain an electricity result.
The whole PC contributes to the reading: processor, graphics hardware, memory, storage, fans, power supply and anything else plugged into the measured outlet. A machine may draw power even when encoding is light, and two applications can use different parts of the same PC. A CPU reading or a GPU percentage describes activity, not the energy taken from the wall over a given period.
There is no published apples-to-apples wattage result in the sources reviewed for the same PC, video, encoder and YouTube stream run in both applications. That means a claim such as “FFmpeg uses less power” or “OBS is more efficient” would be unsupported without a specified test. Treat your result as a finding about your hardware and configuration, not a software-wide rule.
OBS itself cautions that requirements depend on encoder, resolution, frame rate and scene complexity; meeting basic system requirements does not guarantee that a computer can stream a particular workload. Its system requirements guidance is a useful reminder to distinguish a general capability from the demands of your actual scene. For a practical look at one demanding case, see this guide to handling encoder overload in a 4K 60fps loop.
Match resolution, frame rate and stream conditions
A useful comparison holds the streaming job steady while changing the application. Use the same PC and power profile, the same source video and audio, and the same output resolution, frame rate and bitrate. Send both runs to the same destination under comparable network conditions. If a setting cannot be matched, note the difference rather than presenting the result as a clean OBS-versus-FFmpeg comparison.
YouTube’s live encoder guidance recommends CBR and RTMPS. Use the current YouTube encoder settings guidance when choosing output settings, and record what you actually used in each programme. Platform recommendations and software options can change, so check the current official page before a test rather than relying on an old preset copied from a forum.
The content also matters. Use a representative loop, not a still image in one test and a moving video with audio in the other. Motion, source format and audio processing can alter decoding and processing work. If your channel uses a static picture with a radio feed, test that real combination; if it runs devotional video with titles and transitions, include those elements consistently.
Keep anything outside the stream stable as well. Avoid running updates, backups or downloads during one run but not the other. Do not change room cooling or connect extra equipment halfway through. If the display is not needed for an unattended broadcast, leave it off in both tests; the U.S. Department of Energy advises turning monitors off when a networked computer must remain on. Its computer energy guidance provides that distinction between a running computer and an unnecessary display.
Decide in advance what you are measuring. For a PC-only comparison, connect the PC to the meter and keep the display outside the measured load. For a full desk or small studio, include the same display, speakers or other equipment in both runs. The reading is meaningful only for the set of devices you consistently include.
Account for encoder and processing paths
First identify how each programme encodes. OBS can use its software x264 encoder or a supported hardware encoder. The OBS Project explains that hardware encoding transfers work from the CPU to a specialised GPU component and generally recommends it for performance reasons. That describes where encoding work is done; it does not prove that total wall-energy use will be lower on every PC. A hardware-encoding overview from OBS sets out the distinction and its qualifications.
FFmpeg is configurable too. Its documentation includes hardware-encoding and hardware-acceleration options, alongside software paths. Compare equivalent goals where the machine supports them: for example, software encoding in both applications, or compatible hardware encoding in both. If you deliberately compare OBS hardware encoding with FFmpeg software encoding, the result answers which of those two complete configurations used less energy, not which application is inherently more efficient. FFmpeg’s official documentation is the source for its available options; exact support depends on the hardware and software build in use.
Write down more than the encoder label. Record the selected encoder, preset or quality mode, hardware acceleration choice, filters, scaling and any other processing. An OBS scene with animated overlays and several filters is not equivalent to a bare FFmpeg loop. OBS renders and composites scenes, and its encoding performance troubleshooting notes discuss how scene complexity and competing GPU work can affect the workload.
This does not mean every scene element must be removed. It means you should test the actual channel job if your decision is about a real broadcast. A simple controlled run can help isolate application behaviour, while a second run with your finished overlays and audio can show the energy demand of the production you intend to keep online. Label those as separate tests.
Quality must also be acceptable. A low-power result is not a useful choice if it drops frames, fails to deliver the required bitrate or produces a visibly poor stream. Match the intended output quality as closely as you can, and include any trade-off in the report. If you cannot make settings equivalent, describe that limit clearly rather than forcing a simplistic winner.
Measure cumulative energy at the wall
Use a plug-in electricity meter that reports accumulated energy, typically in kWh, rather than relying only on a momentary watt display. Check its electrical rating, outlet compatibility and ability to log or retain a cumulative reading. The meter measures consumption; it does not reduce it. A display showing watts at one instant can be useful context, but it cannot substitute for the energy accumulated during a fluctuating stream workload.
The U.S. Department of Energy’s guidance on measuring standby power states that when consumption fluctuates, energy should be measured over time and divided by the measurement period to determine average power. Although that procedure addresses standby measurements rather than a live-PC comparison, the underlying interval approach is relevant: record energy across a period, not just a snapshot. Its specified accuracy and resolution requirements are for that standby procedure, not a guarantee that a consumer plug meter meets them or a claim about streaming workloads.
For each run, note the cumulative kWh at the start and end of the measurement interval. Let the system settle after launching the stream, then begin the interval and keep its duration equal between tests. Choose a period long enough to include ordinary fluctuations in your workload; there is no magic interval that makes every test representative. Record the actual elapsed time rather than assuming the planned duration was exact.
A simple log makes the comparison reproducible:
| Record for each run | Why it matters |
|---|---|
| Meter make or model and measured devices | Defines the instrument and what the reading includes |
| Start and end energy readings, plus elapsed time | Provides cumulative energy and the basis for average power |
| PC, operating-system power profile and software versions | Identifies the hardware and software context |
| Source file, output settings, encoder and processing | Shows whether the stream jobs were matched |
| Network destination and any interruption | Makes delivery differences visible |
| Background activity or unusual conditions | Helps explain readings that may not represent routine operation |
If practical, repeat the runs and alternate their order. Running OBS first on one day and FFmpeg much later can confound the result with updates, room temperature or other background changes. Keep notes of failed or interrupted stream periods; do not silently remove them. If you need to exclude a run because the test conditions changed, say why and repeat it under the planned conditions.
Compare whole-system results
Use the cumulative energy reading as the main comparison. Average watts are useful for communicating the rate of consumption, but they come from that energy reading and the elapsed interval. Calculate them as:
Average watts = measured kWh ÷ elapsed hours × 1,000
For example, if a meter records an energy difference of E kWh over H hours, the average is E ÷ H × 1,000 watts. This is a formula, not a sample measurement. Do not fill it with invented readings or infer the missing value from a CPU or GPU utilisation graph.
Compare both kWh and calculated average watts for the same duration. If one run lasted longer, compare the average rate only after using its actual elapsed time, and retain the original energy and duration in your notes. A tiny difference may be smaller than the meter’s uncertainty or ordinary run-to-run variation. Without a meter specification and repeat tests, avoid claiming a precise advantage based on a marginal reading.
Also check whether each run delivered the intended stream. Note dropped or failed intervals, encoder warnings, unexpected quality changes and connection interruptions. A lower energy reading during a run that did not maintain the intended output is not a like-for-like success. If you are troubleshooting a demanding broadcast, the encoder overload guide can help separate a performance problem from an energy measurement question.
The most useful conclusion is specific: “On this PC, with this file and these settings, this run used less measured energy over the interval.” Include the meter, measurement duration, software versions and encoder paths so another person can understand the scope. Do not turn that into a universal claim about all OBS or FFmpeg streams.
Turn measured energy into cost
Once you have a measured average, estimate the electricity cost using your own tariff. First extrapolate cautiously: average kW multiplied by 8,760 hours gives an annual kWh estimate for continuous operation. This is a projection from the measured interval, not a year-long test. A channel that is down for maintenance or uses a different schedule will consume a different amount over a year.
Multiply the estimated kWh by the applicable per-kWh charge on your electricity bill to estimate energy cost. Use the charge relevant to your location and billing arrangement, and keep any fixed fees or taxes separate if you are comparing only the electricity used by the PC. Tariffs vary, so a cost calculated with somebody else’s rate is not a reliable estimate for your bill.
For two tested configurations, compare their measured kWh over equal intervals first, then apply the same tariff to each. If the difference is small relative to meter uncertainty or repeat-run variation, treat the result as inconclusive for practical purposes rather than promising a saving. Check again after changing the encoder, adding scene elements, upgrading hardware or changing the stream output.
This is also why a percentage difference without its base reading is unhelpful. Give the energy readings, interval, system boundary and tariff assumption. That lets you revise the estimate when your electricity price or operating schedule changes.
Choose the setup that fits the job
If you already run OBS for scenes, overlays or switching between sources, the relevant test is the complete OBS production you intend to leave running. If you only need to loop a prepared file and prefer a command-line workflow, FFmpeg may suit that task, provided you can configure and monitor it reliably. In either case, use the measured energy alongside output quality, stream continuity and the effort required to maintain the setup.
For some channels, keeping a home PC on all night is the larger operational concern: the machine must remain powered, and a local stream can stop if the PC or connection does. StreamNeo addresses that specific always-on burden by taking an uploaded video and running it as a YouTube live stream after you provide the stream key, so your own computer can be switched off. It is YouTube-only, and it does not change the need to check your content rights or the platform’s current rules.
A cloud-run stream is not an OBS-versus-FFmpeg test on your PC, so do not compare it using the PC-only figures above. It is a separate operating choice to assess against your workflow and costs. If you are deciding between a local computer and a hosted approach, this article on running a prerecorded YouTube stream without OBS on Windows may clarify what the local route involves. For a simple radio-style setup, the guide to YouTube Live settings for a 24/7 stream with a static image covers a different workload that you may want to test on its own.
Before committing, compare the operating options on the pricing page. When the file and channel are ready, start free — 24-hour trial, no card.
FAQ
Does OBS or FFmpeg use less electricity?
There is no universal winner supported by an apples-to-apples benchmark for this exact workload. Measure cumulative wall energy on your PC with matched settings and record the encoder and processing path for each run.
Can CPU or GPU utilisation tell me which uses fewer watts?
No. Utilisation is not a measurement of whole-system energy, and it does not account for the rest of the PC or how long the workload runs. Use a meter that records cumulative energy over an interval.
Should I compare hardware encoding in one programme with software encoding in the other?
You can, but that compares two configurations rather than isolating the applications. For a fairer software comparison, match encoder paths and output goals where your hardware and software support them, then document any differences.
How do I estimate the annual cost of a 24/7 setup?
Convert the measured interval into average watts, extrapolate average kW across 8,760 hours, then multiply the resulting estimated kWh by your own per-kWh tariff. It is an estimate from a measured period, not proof of what the PC will use over a whole year.