If you only want to repeat a YouTube video while you watch, you do not need a refurbished desktop or a cloud VM: YouTube has a loop control in its player. If you want a machine to keep a remote browser open or want to broadcast prerecorded material as a continuous YouTube Live stream, those are different jobs, with different costs.
There is no universal cheaper winner between a desktop and a VM. The answer depends on what must keep running, the computer’s actual power draw and local electricity price, and the VM’s size, region, storage and network use. Start by naming the job before comparing bills.
First decide whether you are watching or broadcasting
YouTube’s normal player can repeat an individual video or a playlist. On a computer, right-click the video and choose Loop; YouTube’s official instructions for looping videos and playlists also cover the available controls. For ordinary viewing, playback happens on a device you already have. The relevant question is whether that device can stay available, not whether you should rent a server.
Leaving a video open in a browser is not the same as sending a live broadcast to your channel. A viewer watching a repeated video sees the YouTube watch page. A continuous live stream appears as a live broadcast and has to be produced and sent to YouTube Live. Do not cost a browser VM as though it were automatically a complete live-streaming system.
There are three plausible meanings behind “looping YouTube videos”:
| Job | What keeps running | What you are paying to keep available |
|---|---|---|
| Watch a video repeatedly | YouTube player on your existing device | Usually no additional machine, unless you need a dedicated device |
| Keep remote browser playback going | A VM, operating system and browser | Compute, storage, network and any applicable software costs |
| Broadcast prerecorded material as a live stream | A playout and encoding workflow that sends a broadcast to YouTube | The production workflow, its operating time, and any associated compute or service costs |
A VM that opens a browser may suit remote access, but it does not become a broadcast workflow just because it plays a video. If your goal is a channel that is live around the clock, first decide how the videos will be assembled, encoded and sent to YouTube. The practical steps for building an always-on channel are a different subject from repeating a video in the player; see this guide to creating an always-on music channel on YouTube.
When a desktop or VM is relevant
A dedicated refurbished desktop can make sense when you need a physical computer on site: perhaps it is connected to a display, used by staff, or runs software and peripherals that are awkward to access remotely. You buy the hardware once, but you accept responsibility for its power, operating system, updates, physical environment and recovery if it stops.
A cloud VM is relevant when you need a remotely accessible computer or a particular process to run without leaving a desktop in your room. You can access it over the network, but the hourly compute figure is only one part of its cost. A small VM is not automatically a suitable desktop replacement, and a browser workload may behave differently from a simple background task.
For a live broadcast of prerecorded material, compare either approach with the actual production workflow. A local desktop might run an encoder and send the stream continuously; a VM can do something similar if it is configured with adequate compute and network capacity. A dedicated playout service may instead take an uploaded file and keep the broadcast running without your home computer remaining on. That is a separate service category, not a cheaper form of YouTube’s loop button.
If you are considering a live playlist from a machine you manage, the distinction between playing a playlist and encoding a stream matters. This walkthrough of continuous YouTube Live with VLC playlist repeat is relevant to the broadcast case, not ordinary viewing. Likewise, a cloud streaming setup may need choices around formats and conversion; our explanation of what transcoding does for streaming helps identify that work before you compare hardware.
What the e2-micro hourly figure calculates to
Google Cloud’s general-purpose pricing page lists an on-demand e2-micro compute rate of $0.008376428 per hour in USD, as listed on Google Cloud’s site in September 2026. Multiplying that hourly rate by an illustrative 730 hours gives approximately $6.11 for compute alone, as calculated from Google Cloud’s listed rate in September 2026. That is an arithmetic illustration, not a quoted monthly bill or a promise that this configuration will run your workload well.
The 730-hour calculation is a convenient continuous-runtime assumption for comparing the arithmetic, not a statement about every month’s duration or your billable usage. The cited price is a USD reference. Google Cloud offers prices by region and consumption model, so check the current general-purpose Compute Engine pricing and your intended location before using it in a budget.
The e2-micro is also a constrained reference point, not an evidenced equivalent to a refurbished desktop running a browser continuously. Google documents it as a shared-core configuration with two vCPUs visible to the guest and 1 GiB of memory, while its total sustained CPU capacity is 0.25 vCPU. In other words, the guest operating system’s count of two does not mean two full physical cores are reserved for your work. Shared-core machines time-share CPU capacity.
That distinction matters if your task loads a browser, decodes video or runs an encoder. A low compute price is useful only if the machine can perform the task acceptably. No browser-performance or reliability test establishes that an e2-micro is suitable for continuous remote playback, and it should not be presented as equivalent to a desktop. If you need a larger VM, price that actual machine type and region instead of extrapolating from the smallest example.
Add the cloud charges beyond compute
The $6.11 figure covers only the stated hourly compute multiplication. Google’s pricing materials describe Compute Engine costs as involving instances, networking and storage; persistent disk is charged separately. Google’s VM pricing information and calculator are the right places to build a quote for a specific deployment. A compute-only figure will understate the bill whenever the workload uses additional resources that incur charges.
List what your particular setup needs. A VM usually needs a boot disk, and a media workflow may need space for source files or temporary output. The amount and type of persistent storage affect the charge. If you upload a large video, retain several files, or keep logs and other data, do not assume the hourly VM rate includes all that storage.
Network use needs a separate check too. Downloading source material and sending data out of a cloud region may be priced differently from compute. For remote browser playback, the video viewed through the browser can involve network traffic; for a live broadcast, outbound stream data is part of the workflow. The amount, route and applicable pricing depend on where resources sit and how the setup is used. Do not invent an egress bill from the compute rate alone.
There may also be software or licence charges depending on the operating system, tools and account arrangement. Whether they apply depends on the actual configuration, so put them in the estimate only after checking the relevant vendor terms. Compare equivalent periods and usage: a machine left on continuously, a VM stopped when idle, and a service billed by a different unit are not directly comparable without adjusting for operating time.
Before launching, record the machine type, region, hours, disk type and size, expected network traffic, and any applicable software costs. Recheck the estimate if the job changes, such as moving from one browser tab to video encoding or keeping more source files online. Google’s price page and calculator can turn those inputs into a more meaningful estimate than the headline hourly rate.
Estimate desktop electricity and ownership
A refurbished desktop’s running cost starts with measured average power, not the wattage printed on its power supply. If the computer averages W watts and runs H hours, energy use in kilowatt-hours is W × H ÷ 1000. Multiply that result by your electricity tariff per kWh to estimate the energy charge for the same period.
For continuous operation, use the actual hours in your comparison period. At 730 hours, the formula is average watts × 730 ÷ 1000 kWh. This is a formula, not a claim about how much any refurbished desktop consumes. A monitor left on adds to the load; switching it off can change the estimate. Measure the complete arrangement you intend to use, including any display that must stay lit, rather than treating a monitor as free.
The purchase price is another part of ownership. For a simple comparison over a chosen period, add the purchase cost, electricity and expected maintenance. You can also show the purchase amount separately from recurring energy costs, or spread it over the useful life you expect; state which treatment you use. A desktop acquired cheaply may still cost more to run in a high-tariff location, while a higher purchase cost can be more reasonable if the computer serves other work as well.
There is no reliable desktop price, standard power draw or electricity tariff established for this comparison. Those inputs vary by model, condition, local market and household tariff. Obtain a quote for the actual refurbished machine, check its condition and warranty, and measure its average draw over representative use with a suitable power meter. Do not substitute a product’s maximum power-supply rating for measured average consumption.
Include maintenance and the practical costs that matter to you. A refurbished machine may need a replacement drive, battery or fan, or attention after a power interruption; none of these is certain, so treat them as risks or observed costs rather than fixed assumptions. Consider whether you already own a monitor and peripherals. If you must buy them solely to keep a video running, include their purchase and energy costs.
Compare the same workload and reliability needs
A fair comparison gives desktop and VM the same job, operating hours and time horizon. If one option merely repeats a video locally while the other runs a remote browser continuously, their costs answer different questions. If the task is a live stream, compare two complete ways of producing and sending that stream, rather than comparing a browser-playing VM against a desktop encoder.
For playback, note whether you need remote access, an on-site screen, sound, or a user logged in. The ordinary YouTube player is designed for viewing, and its loop control does not require continuous broadcast. A remote browser can be useful if you need to reach a session from elsewhere, but include the browser’s resource demands and the cloud network costs. A desktop may be simpler if it is already available where the display is needed.
For a live broadcast, note the media format, resolution, frame rate, encoding method and whether the output is a continuous stream. Those requirements shape the computer or service needed. If you are developing an OBS workflow, for instance, adding on-screen information is part of the production task, not a cost of YouTube’s normal loop mode; see the guide to adding a clock and ticker to an OBS 24/7 stream if that is relevant to your setup.
Reliability is not just a price line. A physical desktop relies on local power, network access, hardware condition and someone being able to troubleshoot it. A VM avoids leaving a computer in your room, but it still depends on a correctly configured instance, account access, networking and the service’s operation. Neither option should be assigned a guaranteed uptime from this comparison; no reliability test was conducted for these configurations.
Write down how much interruption you can tolerate and what recovery looks like. Would someone notice a stopped browser? Does the stream need to be restarted manually, and who can do it? Does the machine need automatic restarts or monitoring? These operational needs may justify a different setup from the least expensive compute line. If you are comparing an uploaded-video playout service, assess its supported workflow and terms separately rather than implying that all cloud options behave alike.
Choose for the actual job
If you simply want to watch one video repeatedly, use YouTube’s player loop on a device you already have. A separate desktop or VM adds cost and maintenance without solving a necessary broadcasting problem. If the player control is not available in the way you watch, check YouTube’s current instructions and the device’s own playback options before renting compute.
If you need a dedicated local screen, or a physical computer for other tasks, price a refurbished desktop using a real quote, measured power and your local tariff. Its costs are easier to understand once you include the upfront hardware and what it can do beyond the video. It may be the practical choice when you need the machine on site, but its ongoing energy and maintenance are yours to manage.
If you need remote browser access, select a VM based on the real browser workload rather than assuming e2-micro is adequate. Build an estimate with compute, disk, network and any applicable software, using the region and operating time you intend to use. The $6.11 compute-only calculation is a useful reference point for one listed rate, not a monthly total to put beside a desktop purchase price.
If your actual requirement is a continuous YouTube Live broadcast of prerecorded material, cost the complete broadcast workflow. A desktop or VM can be part of that workflow, but it must be configured to send a live stream and remain recoverable. For creators who want the uploaded video to keep broadcasting while their own computer is off, StreamNeo removes the specific burden of leaving and recovering a home machine for that continuous playout; it is a YouTube-only service and does not turn normal player looping into a live stream.
A short worksheet prevents false comparisons: write down job, hours, period, desktop quote, average watts, tariff, VM size, region, disk, network, software and recovery needs. Leave unknowns visible rather than filling them with guesses. Once the missing inputs are sourced, total each option for the same period; if you lack credible quotes, the honest conclusion is that a break-even figure cannot yet be calculated.
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
Can I loop a YouTube video without a VM?
Yes. YouTube’s player offers a Loop control for repeating a video, and playlists can also be looped. That is normal playback on a device, not a live broadcast, so a VM is not required merely to use the feature.
How much does a cloud VM cost to run 24/7?
The cited Google Cloud e2-micro on-demand rate works out to about $6.11 for 730 hours of compute, using the hourly rate listed on Google Cloud’s site in September 2026. It is not an all-in bill: disk, network and applicable software costs may be additional, and prices vary by region and usage model.
Is an e2-micro equivalent to a refurbished desktop?
No equivalence is established here. Google documents e2-micro as a shared-core machine with 1 GiB memory and 0.25 fractional vCPU capacity, so check whether the workload fits instead of treating the low hourly price as desktop performance.
Which option is cheaper for a continuous YouTube Live stream?
There is no universal winner without a specific desktop quote and power measurement, local electricity tariff, VM configuration and network estimate. Compare the complete broadcast workflow over the same period, including recovery needs; ordinary player looping is not the same workload.