Neither Google Compute Engine nor AWS EC2 is universally cheaper or more reliable for a 24/7 YouTube stream. The better fit depends on your region, VM and operating system, whether you are encoding or relaying video, the stream bitrate, outbound-transfer charges, and how you recover from failures. Compare both providers using the same workload in their calculators, then test the chosen VM with your actual encoder settings. If you would rather not manage a VM, StreamNeo is an alternative to try first: it runs uploaded videos to YouTube from the cloud, at any quality up to 4K 60fps for one flat price per slot, with the first day free.
What you are comparing
Compute Engine and EC2 are virtual machines, not turnkey YouTube streaming services. You choose and maintain a VM, install or configure an encoder or relay, provide the video source, and send the stream to YouTube. That gives you control over the software and architecture, but it also means you are responsible for sizing, billing, monitoring and recovery.
First establish which job the VM must do:
- Loop a prerecorded video: the source is a file or playlist. The VM may need to read and relay it, or encode it if the output profile differs from the source.
- Encode a live source: the VM must handle the input and encode it continuously. Codec, resolution, frame rate and software-versus-hardware encoding affect the resources required.
- Relay an already-encoded feed: the VM forwards a stream rather than doing the full encode. Its network path and the relay software matter, but the workload differs from live encoding.
A VM that can send the target bitrate is not necessarily powerful enough to encode the video. Conversely, a published network ceiling does not guarantee stable throughput to YouTube. Treat compute capacity and network capability as separate checks.
Google Compute Engine vs AWS EC2 at a glance
| Factor | Google Compute Engine | AWS EC2 |
|---|---|---|
| What determines VM cost | Machine, region, runtime, disk and network configuration; use the calculator for the intended setup. Google’s product overview advertises an e2-micro starting price, not a recommended encoder size. Google Cloud Compute Engine | Instance type, operating system and runtime, with disk and network charges separate. Instances are billed from launch until stopped or terminated; Linux and several other listed systems use per-second billing with a 60-second minimum. AWS EC2 On-Demand Instance Pricing |
| Outbound-transfer information in the cited provider pages | The product overview describes up to 200 GB per month outbound on standard network tier and premium-tier outbound transfer starting at $0.08 per GB. Exact charges depend on configuration and location. Google Cloud Compute Engine | The EC2 pricing page identifies 100 GB per month of internet data transfer out free across AWS services and regions, except China and GovCloud. The allowance aggregates usage across the stated services, so it is not necessarily all available to one EC2 stream. Check current scope and rates for your account and region. AWS EC2 On-Demand Instance Pricing |
| Network ceiling | Per-instance egress limits vary by machine series and destination. Google describes a general limit around 2 Gbps per vCPU, with exceptions; its table lists shared-core E2 at 2 Gbps. These are ceilings, not sustained-throughput promises. Compute Engine network bandwidth | Use the chosen instance’s current specifications and test its route to YouTube. The cited EC2 pricing page does not establish a universal throughput figure for YouTube streaming. AWS EC2 On-Demand Instance Pricing |
| Reliability winner for this use | Not established by the cited sources as a universal winner. | Not established by the cited sources as a universal winner. |
The table is not a like-for-like quote: the providers’ billing definitions, regions, machine types and network terms differ. Enter the same operating system, expected hours, disk needs, region and transfer estimate in each provider’s calculator. Recheck the live quote before committing; published allowances and rates are scoped and may change.
#1 Best Overall
- Apple-designed M1 chip for a giant leap in CPU, GPU, and machine learning performance
- 8-core CPU packs up to 3x faster performance to fly through workflows quicker than ever*
- 8-core GPU with up to 6x faster graphics for graphics-intensive apps and games*
- 16-core Neural Engine for advanced machine learning
- 8GB of unified memory so everything you do is fast and fluid
Estimate the stream’s outbound data before pricing
A continuously running feed adds up even at a modest bitrate. A useful first estimate is:
Outbound payload in GB ≈ bitrate in Mbps × stream hours × 0.45
Rank #2
- MINI PC COMPUTER OFFICE LIGHT GAMING - GMKtec Nucbox G10 Series is equipped with the Ryzen 5 3500U, a 64-bit quad-core mid-range performance x86 mobile microprocessor. This processor is based on AMD's Zen+ microarchitecture and is fabricated on a 12 nm process. The 3500U operates at a base frequency of 2.1 GHz with a TDP of 15 W and a Boost frequency of 3.7 GHz. This APU supports up to 32 GB of dual-channel DDR4-2400 memory and incorporates Radeon Vega 8 Graphics operating at up to 1.2 GHz. 20% Multi-core Performance increase over previous Ryzen 3 models such as 4300U. 35% performance increase over the Intel N-series N95/N97/N150.
- RYZEN 5 3500U vs RYZEN 3 4300U COMPARISON - Why Choose Ryzen 5 3500U: Better multi-threaded performance: More threads, better suited for multitasking and demanding applications. Better graphics: With Vega 8, it's superior for casual gaming, video playback, and GPU-intensive tasks. Overall higher performance: Higher boost clock and better ability to handle a variety of workloads, from light gaming to productivity tasks. So, if you're looking for a more balanced processor with stronger multitasking capabilities and better GPU performance, the Ryzen 5 3500U would be the clear choice.
- 16GB DUAL CHANNEL DDR4 + 512GB SSD - Installed with DDR4 16GB SO-DIMM RAM Dual Channel (2x8GB) and a 512GB SSD, the Nucbox G10 mini pc supports memory expansion to 64GB RAM. Featured with Dual M.2 2280 PCIe 3.0 slots, supports dual storage slot expansion to 16TB SSD (2*8TB). (Upgrades not included) This model supports a configurable TDP-down of 12 W and TDP-up of 35 W.
- UNLEASH RAW PERFORMANCE MODE 25W - Dominate demanding tasks with the AMD Ryzen 5 3500U processor. When switched to Performance Mode in the BIOS (press "Esc" key repeatedly during boot, save then exit), this mini PC delivers superior multi-core processing power, significantly outperforming Intel N-series chips in CPU-intensive applications, multitasking, and creative workloads.
- MINI DESKTOP COMPUTER WITH TRIPLE DISPLAY SCREEN - Nucbox G10 integrates AMD Radeon Vega 8 1200 MHz GPU to deliver powerful graphics processing power to easily handle video editing, and playback, or casual gaming. And it can connect to 3 display screens simultaneously via HDMI 2.1 TMDS/ DPv1.4/ TYPE-C.
This uses decimal gigabytes and estimates video payload only; actual transfer can differ because of protocol overhead, restarts and the exact stream duration. For a 30-day month at 24 hours per day, 720 hours at 4 Mbps is about 1,296 GB of payload. A higher bitrate scales the estimate proportionally. Compare that estimate with each provider’s applicable transfer pricing and allowance; do not assume the monthly allowance covers the whole stream.
This is the stream sent from your VM to YouTube. It is not the same cost profile as a service that sends the video onward to viewers itself. If you are only pushing one feed to YouTube, do not use a viewer-distribution architecture as the price of a single VM: AWS’s cited Live Streaming on AWS example combines MediaLive, MediaPackage and CloudFront, and its approximately $1,505.60-per-hour estimate assumes roughly 10,000 viewers and stated US East (N. Virginia), bitrate, cache and highest-bitrate conditions. It illustrates a broader distribution pipeline, not an EC2-versus-Compute-Engine quote for one encoder. AWS Live Streaming on AWS implementation guide
Windows Errors? Fix Them Before They Spread
Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallOutdated Drivers Are Slowing You Down
One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchRank #3
- 6-core Intel Core i5 processor
- Intel UHD Graphics 630
- 8GB 2666MHz DDR4
- Ultrafast SSD storage
- Four Thunderbolt 3 (USB-C) ports, one HDMI 2. 0 port, and two USB 3 ports
Choose a YouTube profile, then size the VM
YouTube’s encoder guidance recommends RTMPS, the secure extension of RTMP, and a two-second keyframe interval, not exceeding four seconds. Its H.264 bitrate recommendations vary by resolution and frame rate. These are YouTube ingest recommendations—not a VM sizing guide or a guarantee of a stable route. AV1 and H.265 have separate bitrate ranges; do not apply the H.264 figures to those codecs. See YouTube’s live encoder settings, bitrates and resolutions.
| H.264 profile | YouTube recommended bitrate |
|---|---|
| 240p–720p at 30 fps | 4 Mbps |
| 720p at 60 fps | 6 Mbps |
| 1080p at 30 fps | 10 Mbps |
| 1080p at 60 fps | 12 Mbps |
| 1440p at 30 fps | 15 Mbps |
| 1440p at 60 fps | 24 Mbps |
| 2160p at 30 fps | 30 Mbps |
| 2160p at 60 fps | 35 Mbps |
Use the chosen profile to estimate transfer and check outbound capacity. Then size the VM for the actual source and encoding load. A looped file, an already-encoded relay and a live software encode are not interchangeable workloads; no published source establishes a specific VM size for any of them. Start with a candidate appropriate to your workflow, run the encoder at the intended profile, and observe CPU or GPU use, dropped frames and sustained network throughput before treating the configuration as production-ready.
Rank #4
- SIZE DOWN. POWER UP — The far mightier, way tinier Mac mini desktop computer is five by five inches of pure power. Built for Apple Intelligence.* Redesigned around Apple silicon to unleash the full speed and capabilities of the spectacular M4 chip. With ports at your convenience, on the front and back.
- LOOKS SMALL. LIVES LARGE — At just five by five inches, Mac mini is designed to fit perfectly next to a monitor and is easy to place just about anywhere.
- CONVENIENT CONNECTIONS — Get connected with Thunderbolt, HDMI, and Gigabit Ethernet ports on the back and, for the first time, front-facing USB-C ports and a headphone jack.
- SUPERCHARGED BY M4 — The powerful M4 chip delivers spectacular performance so everything feels snappy and fluid.
- BUILT FOR APPLE INTELLIGENCE — Apple Intelligence is the personal intelligence system that helps you write, express yourself, and get things done effortlessly. With groundbreaking privacy protections, it gives you peace of mind that no one else can access your data — not even Apple.*
Make a fair provider comparison
- Fix the workload. Record whether you are looping a file, encoding a live input or relaying an encoded feed; set codec, resolution, frame rate and target bitrate.
- Choose a region and operating system. Use the same region and OS assumptions for each estimate where possible. Note any difference you cannot match.
- Estimate hours and transfer. Use the bitrate and expected monthly running hours to estimate payload, then allow for overhead and restarts. Keep stream-to-YouTube traffic distinct from viewer distribution.
- Price the full VM setup. Include instance runtime, boot and data disks, and applicable IP or network resources—not just a headline VM rate. Enter the transfer estimate and verify the current region-specific terms in each provider’s calculator.
- Run a sustained test. Monitor encoder load, dropped frames, throughput and process restarts at the target profile. Google notes that actual bandwidth may be lower than its ceiling because of machine family, routing, NIC configuration, drivers, packet size, protocol overhead, flow count, guest OS settings, congestion and disk-I/O competition.
- Test recovery deliberately. Confirm how the encoder process starts after a VM reboot, how you learn that a stream has stopped, and how it reconnects. A VM restart or encoder crash can interrupt the stream even if the cloud provider’s infrastructure remains available.
This method compares your workload rather than provider slogans. There is no evidence in the cited material for a universal price or end-to-end uptime winner between the two clouds.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Keep the stream recoverable
A 24/7 stream depends on both the VM and the software process sending video. Plan for failures at each layer:
Best Value
- LITTLE DO-IT-ALL — Mac mini packs pure power into a small, five-by-five-inch desktop as the M6 chip delivers next-level AI capabilities. Mac mini features 2.5Gb Ethernet with support for Wi-Fi 7* and Bluetooth 6, with ports on the front and back.
- M6 CHIP — Everything you do on Mac mini feels more responsive with the M6 chip and its next-generation CPU. Fly through AI workflows with up to 4.8x faster AI performance,* thanks to a Neural Accelerator in each GPU core, faster unified memory, and a Dual 16-core Neural Engine.
- CONNECT IT ALL — Features three Thunderbolt 4 ports, an HDMI port, and a 2.5Gb Ethernet port in the back, and two USB-C ports and a headphone jack in front. Supports up to three external displays. With the Apple-designed N1 wireless chip for Wi-Fi 7* and Bluetooth 6.
- A POWERFUL PLATFORM FOR AI — Apple silicon is designed to run demanding AI workflows like using huge LLMs, directly on device. And Apple Intelligence* helps you write, express yourself, and get things done effortlessly, while Siri AI* is your profoundly capable assistant — all with groundbreaking privacy protections.
- A POWERFUL PLATFORM FOR AI — Apple silicon is designed to run demanding AI workflows like using huge LLMs, directly on device.
- Encoder or relay exits: configure a supervisor or equivalent restart behavior, and verify it by stopping the process during a test.
- VM restarts: make the streaming process start again when the operating system boots; confirm the source file or input is available after reboot.
- YouTube disconnects: verify how the encoder reconnects and whether the stream resumes as intended. Keep a way to notice repeated disconnects rather than assuming automatic reconnection is working.
- Resource saturation: watch CPU/GPU load, disk I/O and network throughput together. A bottleneck can present as dropped frames or an unstable feed.
- Credentials: treat the YouTube stream key as a secret. Do not expose it in public logs or share it; replace it in YouTube if it is compromised.
These are operational checks, not a claim that either provider has a particular uptime advantage. The recovery design and the stream profile you validate matter to the result.
Or let it run in the cloud
If your goal is simply to keep uploaded videos playing on YouTube without maintaining a VM, StreamNeo is the alternative to try first. Upload a recording or build a playlist, add your YouTube stream key once, and go live; StreamNeo loops the upload from its cloud service, so your computer and home connection do not have to stay on. It supports uploaded video, not a live camera, and streams to YouTube.
Quick Recap
- Nothing has to stay on at home.
- Any uploaded quality up to 4K 60fps streams as made, at one price per slot, with no re-encode or quality tiers.
- Automatic recovery if YouTube drops the stream.
- The first day is free with no card, one free day per account.
- Monthly: $9.99 per month.
Start your free StreamNeo day.
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
