A 24/7 YouTube stream has no universal monthly price on Google Cloud Compute Engine or on a mini PC. You need to specify the stream settings, cloud machine and region, or the mini PC’s measured power draw, then include the costs that apply to each setup.
The useful comparison is a monthly operating estimate, not a single headline figure. This guide uses 730 hours as a common comparison period and gives you the calculations to fill in with current prices, a real workload and your local electricity rate.
Why the monthly price depends on your inputs
A Compute Engine bill is not simply “the cost of a VM”. The selected machine type and region set the compute rate, while persistent disk, outbound network transfer and any other billable resources can add charges. Google Cloud’s general-purpose machine pricing lists prices by machine family and region; check the current listing for the configuration you intend to use.
A mini PC has a different cost shape. Electricity is a recurring expense, while buying the computer is usually an upfront cost. You may also need to account for its internet connection, peripherals, replacement parts or the value of your time maintaining it. Whether those belong in your comparison depends on whether the computer and connection are already in use for other purposes.
The workload matters to both options. A static devotional image with audio, a 1080p ambient video and a 60 fps gameplay feed do not necessarily ask the encoder to do the same work. A low VM rate does not show that the VM can encode your chosen stream reliably, just as a mini PC’s advertised specifications do not establish its sustained power use or suitability for your settings.
Keep recurring expenses separate from one-time or shared expenses. That makes the comparison useful even if you already own a computer, or if your cloud project has other workloads that share a disk or network resource.
Set a fair stream and comparison period
Begin with the stream you actually plan to run: video resolution, frame rate, codec, bitrate, whether it includes audio, and whether you are sending a live camera or looping a prepared file. YouTube’s live encoder settings describe supported ingest options and recommended bitrate ranges. For example, its H.264 guidance recommends 5 Mbps for 1080p at 30 fps and 6 Mbps for 1080p at 60 fps. These are settings to consider, not proof that a particular host can encode them.
You are sending an ingest stream, not independently encoding every viewer’s playback copy. YouTube says it transcodes a live stream to create output formats for viewers on different devices and networks. That distinction helps keep the host-side workload in perspective, but it does not remove the need to test your actual encoding settings.
Use 730 hours as a normalised month for the arithmetic below. It is a 30.4-day convention, not the exact length of every calendar month. For a different runtime, replace 730 with the number of hours you expect to run. If a stream is offline for planned maintenance, use the lower runtime; if it must remain on through a full calendar month, calculate that month’s hours separately.
Write down the comparison boundary as well. For example, your estimate might include a VM, a persistent boot disk and forecast outbound transfer, but exclude a Google Cloud monitoring product you do not use. For the mini PC, it might include wall-power electricity and an allocated portion of the existing broadband connection, but show the purchase cost separately. Different boundaries produce different totals, so label them rather than implying one is universally correct.
If you are still choosing a file-based workflow, the practical differences between OBS and FFmpeg for continuous streaming can help you identify what the host must run. The software and settings are part of the workload definition, not an incidental detail.
Select a Compute Engine machine and region
Choose a machine type based on the encoder and stream you will run, then select the region that makes sense for your requirements. Google documents E2 as a cost-optimised general-purpose machine series in its general-purpose machine documentation. That description does not establish that a small E2 configuration can sustain every video encode, nor that it will be cheapest for your particular combination of region and other resources.
Record the exact machine type and region before using a price. Compute Engine rates vary by region and machine family, and pricing can change. Use Google’s current pricing page or the project’s estimator to find the hourly compute price for the selected configuration. Record the currency and the date you checked it. If you quote a price in a published estimate, attribute and date it, for example: “as listed on Google Cloud’s site in September 2026”. Do not carry a remembered price forward as though it were current.
The operating system can influence the overall setup and may affect licensing charges in some configurations. Include any applicable operating-system charge in the estimate rather than assuming every VM has the same treatment. Also note any discounts or commitments only if they genuinely apply to your account and you can explain their conditions. A standard on-demand estimate is easier to compare with a mini PC’s ongoing electricity use than a price that depends on an unmentioned commitment.
Before settling on a small instance, test the selected settings under sustained load. Watch for missed frames, encoder overload, interruptions and whether the VM has enough capacity for any additional tasks. For a file loop, frame-rate conversions and transitions may add work; guidance on handling different frame rates in an FFmpeg playlist may help you avoid mistaking a file problem for a host-capacity problem.
Calculate VM compute for 730 hours
The compute component is straightforward once you have the actual hourly price:
VM compute for the comparison month = selected VM hourly price × 730 hours
For instance, if the pricing page gives you an hourly rate of R in the currency you are using, your compute-only line is R × 730. This is a formula, not a quoted Google Cloud total. Fill in R from the current listing for your exact machine type and region. Do not use a machine-family headline rate if it does not match the selected configuration.
A small table can make the inputs auditable:
| Compute input | What to record |
|---|---|
| Machine type | The exact Compute Engine type, not just the family |
| Region | The region used to look up the rate |
| Hourly compute rate | Current rate and currency, with the date checked |
| Runtime | 730 hours for this comparison, or your actual planned hours |
| Compute subtotal | Hourly rate multiplied by runtime |
This subtotal is not an all-in monthly cloud estimate. It excludes any applicable disk, outbound transfer and other resources unless the quoted rate explicitly includes them. Keep the distinction visible if you use a calculator that combines line items.
A VM can also be billed while it is running even when there is little useful work happening. A stream that needs to remain available overnight may therefore incur the full runtime cost, not merely the hours when somebody is watching. Conversely, if your service reliably stops the VM when the stream is not needed, calculate only the actual billed runtime—but that is no longer a 24/7 broadcast.
Add disk, egress and other cloud resources
List the resources in addition to compute, then check which ones apply to your setup. A persistent boot disk can remain billable while the VM runs; its type and size matter. If you store media in another cloud resource, include it according to the applicable storage rate and retention period. Do not count the same media storage twice if it is already included in the resource estimate.
Network egress requires a careful boundary. The stream sends video from the VM to YouTube, so outbound transfer may be relevant under the applicable Google Cloud pricing and routing rules. Do not assume either that every byte is charged at the same rate or that egress is free. Estimate the transfer volume from the configured bitrate and runtime, then apply current pricing rules for your source and destination. A bitrate is measured in bits per second, while transfer billing is typically expressed in bytes, so convert units consistently and allow for protocol overhead if you are making a detailed forecast.
For orientation, a configured stream bitrate of 5 Mbps sustained across 730 hours implies a substantial transfer volume. Treat that as a workload calculation, not a cloud price: your bill depends on current network pricing, destination, applicable allowances and the precise path. Check the relevant Google Cloud network rates rather than borrowing a transfer price from another region or provider.
Other items may apply if you add them: monitoring, logging, snapshots, static addresses, image storage or separate storage for source files. Include only resources you actually plan to use, but include all that apply. A clear worksheet might look like this:
| Cloud line item | How to estimate it |
|---|---|
| VM compute | Hourly rate for chosen type and region × billed hours |
| Persistent disk | Selected disk size and type × applicable billing period |
| Outbound transfer | Estimated transferred data × applicable current rate |
| Other resources | Each enabled resource × its applicable usage or time |
| Estimated cloud total | Sum of the included lines; state any exclusions |
A total that omits network transfer or disk can still be useful as a compute-only comparison, provided it is labelled that way. Avoid calling it the cost of running the stream overall. Rates and billing details can change, so verify them on the official pricing pages before committing or publishing a figure.
Measure mini-PC electricity under the stream workload
Do not assign a generic wattage to “a mini PC”. Power draw varies with the specific model, codec, resolution, frame rate, cooling, attached devices and what else the computer is doing. The research behind this comparison did not establish an attributable representative measurement for a mini PC continuously encoding a YouTube stream. Measure the actual unit and workload instead.
A plug-in electricity meter can show wall draw, which is more useful for estimating electricity than a processor specification or the power rating on an adapter. Run the intended stream settings for a representative period, including the normal video loop, audio and any other applications that will remain open. If the draw fluctuates, use an average over that period rather than the highest momentary reading. Note what was connected to the meter so you do not accidentally include a monitor or unrelated device in one setup but not the other.
The calculation is:
Electricity cost = average watts ÷ 1,000 × 730 hours × local price per kWh
The conversion from watts to kilowatts is necessary because an electricity tariff is usually expressed per kilowatt-hour. Then multiply by the number of hours and the rate on your electricity bill. If your tariff changes by time of day or usage band, use a rate that reflects the periods when the stream will actually run, or show the tariff assumption explicitly.
As arithmetic illustrations only, a sustained 10 W load uses 7.3 kWh in 730 hours; at 20 W it uses 14.6 kWh. These are hypothetical inputs, not typical mini-PC measurements. To turn either into a cost, multiply the kWh figure by your local price per kWh. For an India-based reader, use the rate applicable to your connection and tariff rather than assuming one national price.
Measure the complete arrangement consistently. If the mini PC needs a USB audio device or storage drive to stream, include those in the measured draw. A display that you switch off after setup may be excluded if it remains off in normal operation. If the computer also serves other household or business tasks, decide whether to allocate all or only part of its electricity to the stream, and state that choice.
Compare the full ownership picture
A useful comparison keeps monthly operating costs and one-time costs in separate rows. Compute Engine may have no local computer purchase in the estimate, but it can have additional cloud resources and still depends on a reliable local connection for management. A mini PC’s electricity calculation excludes the initial purchase unless you add an allocation for it; it also does not make the device free simply because you already own it.
| Cost or condition | Compute Engine | Mini PC |
|---|---|---|
| Main recurring charge | Selected VM compute for billed hours | Measured wall-power use × local electricity rate |
| Additional recurring items | Disk, egress and enabled cloud resources | Internet allocation, if included, and any ongoing maintenance |
| One-time cost | Any setup or media preparation you choose to count | Hardware purchase and any required accessories |
| Capability check | Sustained encode on the selected VM and settings | Sustained encode on the exact computer and settings |
| Operational dependency | Cloud configuration, billing and the stream source file | Local power, cooling, connection and computer upkeep |
If you want to amortise a mini PC purchase, show the method rather than hiding it inside electricity. For example, divide the purchase cost by the number of months over which you expect to use it, then add that monthly allocation to the measured electricity. The useful service life is your assumption, not a universal figure. If the computer already has other uses, you might allocate only a share of the purchase cost; explain the allocation so another reader can reproduce it.
Internet service is another boundary decision. A home broadband bill may remain unchanged whether or not the stream runs, but the stream consumes sustained upload capacity. If the connection is dedicated or you upgrade it for the channel, include that incremental cost. On the cloud side, your home internet is still needed to administer the project, though the video feed itself comes from the VM.
Reliability is not a line item with a universal price. A local setup depends on your electricity supply, router, ISP and the mini PC staying operational. A cloud setup avoids relying on your home computer for the broadcast, but it still depends on configuration, account access, resource availability and YouTube ingest. YouTube advises leaving upload headroom—its guidance recommends 20% above the stream bitrate—and warns that network disruption can break a stream. See its streaming tips and test the actual connection and stream health.
The operational tasks differ too. A local machine needs updates, cooling, restart behaviour and a plan for power or broadband interruptions. A VM needs configuration checks, cost monitoring and a recovery plan. For local Windows setups, a checklist on keeping a 24/7 stream live after restarts is relevant because a restart can affect both availability and how you measure actual runtime.
Turn the estimate into a decision
Build two estimates from your own inputs before choosing. For the cloud, record the selected VM hourly rate, region, runtime, disk, expected transfer and additional services. For the mini PC, record the exact hardware, the measured average watts while streaming, local electricity tariff, purchase cost and any connection cost you intend to allocate. The result should have a recurring subtotal and, separately, a one-time or amortised hardware figure.
Then test capability and operational fit. If the stream settings push the host’s encoder beyond what it can sustain, the lower theoretical operating cost is not useful. If your electricity or broadband is unreliable overnight, a computer at home may need a contingency plan. If you have an already-owned mini PC and spare upload capacity, its incremental cost may be different from buying and connecting a new device. If you prefer not to leave your own computer running, a hosted approach can remove that particular burden; StreamNeo turns an uploaded video into a YouTube live stream that continues without your computer running, which addresses the overnight computer-maintenance problem rather than making every other cost disappear.
Use a trial stream or an unlisted test to check the ingest settings and stream health before relying on the setup. YouTube recommends testing and monitoring; its stream health guidance helps you inspect whether the feed is arriving as expected. A test does not establish future uninterrupted operation, but it can reveal a weak encoder setting or upload connection before you depend on it.
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
Is there a typical monthly price for a 24/7 YouTube stream?
There is no meaningful universal total without naming a cloud configuration or mini PC, workload, region or measured power, and included cost categories. Calculate from your own current VM rate or wall-power measurement, then state what you included and left out.
Can a low-cost Compute Engine VM encode a 1080p stream?
The price of a VM does not establish its encoding capacity. Test the exact machine type, codec, resolution, frame rate and bitrate under sustained load, and watch YouTube stream health for encoder or ingest problems.
How do I calculate mini-PC electricity for a month?
Measure the average wall draw while the actual stream setup is running, divide watts by 1,000, multiply by 730 hours, then multiply by your local price per kWh. The 730-hour period is a comparison convention; use the real hours and tariff if your estimate needs to match a specific bill.
Should I include the mini PC’s purchase price?
Show it separately from recurring electricity. If you want a monthly ownership comparison, state the useful-life or allocation assumption used to spread the purchase cost over time, and keep internet or accessory costs visible rather than hiding them in the power calculation.