Test Bed and Setup

As per our processor testing policy, we take a premium category motherboard suitable for the socket, and equip the system with a suitable amount of memory running at the manufacturer's maximum supported frequency. This is also typically run at JEDEC subtimings where possible. It is noted that some users are not keen on this policy, stating that sometimes the maximum supported frequency is quite low, or faster memory is available at a similar price, or that the JEDEC speeds can be prohibitive for performance. While these comments make sense, ultimately very few users apply memory profiles (either XMP or other) as they require interaction with the BIOS, and most users will fall back on JEDEC supported speeds - this includes home users as well as industry who might want to shave off a cent or two from the cost or stay within the margins set by the manufacturer. Where possible, we will extend out testing to include faster memory modules either at the same time as the review or a later date.

Test Setup
AMD Ryzen 3000 AMD Ryzen 5 3600
Motherboard GIGABYTE X570 I Aorus Pro (1.12e)
CPU Cooler AMD Wraith
DRAM G.Skill FlareX 2x8 GB DDR4-3200 C14
GPU Sapphire RX 460 2GB (CPU Tests)
MSI GTX 1080 Gaming 8G (Gaming Tests)
PSU Corsair AX860i
SSD Crucial MX500 2TB
OS Windows 10 1909

Many thanks to...

We must thank the following companies for kindly providing hardware for our multiple test beds. Some of this hardware is not in this test bed specifically, but is used in other testing.

Hardware Providers
Sapphire RX 460 Nitro MSI GTX 1080 Gaming X OC Crucial MX200 +
MX500 SSDs
Corsair AX860i +
AX1200i PSUs
G.Skill RipjawsV,
SniperX, FlareX
Crucial Ballistix


Scale Up vs Scale Out: Benefits of Automation

One comment we get every now and again is that automation isn’t the best way of testing – there’s a higher barrier to entry, and it limits the tests that can be done. From our perspective, despite taking a little while to program properly (and get it right), automation means we can do several things:

  1. Guarantee consistent breaks between tests for cooldown to occur, rather than variable cooldown times based on ‘if I’m looking at the screen’
  2. It allows us to simultaneously test several systems at once. I currently run five systems in my office (limited by the number of 4K monitors, and space) which means we can process more hardware at the same time
  3. We can leave tests to run overnight, very useful for a deadline
  4. With a good enough script, tests can be added very easily

Our benchmark suite collates all the results and spits out data as the tests are running to a central storage platform, which I can probe mid-run to update data as it comes through. This also acts as a mental check in case any of the data might be abnormal.

We do have one major limitation, and that rests on the side of our gaming tests. We are running multiple tests through one Steam account, some of which (like GTA) are online only. As Steam only lets one system play on an account at once, our gaming script probes Steam’s own APIs to determine if we are ‘online’ or not, and to run offline tests until the account is free to be logged in on that system. Depending on the number of games we test that absolutely require online mode, it can be a bit of a bottleneck.

Benchmark Suite Updates

As always, we do take requests. It helps us understand the workloads that everyone is running and plan accordingly.

A side note on software packages: we have had requests for tests on software such as ANSYS, or other professional grade software. The downside of testing this software is licensing and scale. Most of these companies do not particularly care about us running tests, and state it’s not part of their goals. Others, like Agisoft, are more than willing to help. If you are involved in these software packages, the best way to see us benchmark them is to reach out. We have special versions of software for some of our tests, and if we can get something that works, and relevant to the audience, then we shouldn’t have too much difficulty adding it to the suite.

Turbo, Power, and Latency CPU Performance: System Tests


View All Comments

  • PeachNCream - Monday, May 18, 2020 - link

    Anandtech spends a lot of time on gaming and on desktop PCs that are not representative of where and how people now accomplish compute tasks. They do spend a little time on mobile phones and that nets part of the market, but only at the pricey end of cellular handsets. Lower cost mobile for the masses and work-a-day PCs and laptops generally get a cursory acknowledgement once in a great while which is disappointing because there is a big chunk of the market that gets disregarded. IIRC, AT didn't even get around to reviewing the lower tiers of discrete GPUs in the past, effectively ignoring that chunk of the market until long after release and only if said lower end hardware happened to be in a system they ended up getting. They do not seem to actively seek out such components, sadly enough. Reply
  • whatthe123 - Monday, May 18, 2020 - link

    AI/tensorflow runs so much faster even on mid tier GPUs that trying to argue CPUs are relevant is completely out of touch. No academic in their right mind is looking for a bang-for-buck CPU to train models, it would be an absurd waste of time. Reply
  • wolfesteinabhi - Tuesday, May 19, 2020 - link

    well ..games also run on GPU ...so why bother benchmarking CPU's with them? ... same reason why anyone would want to look at other workflows .. i said tensor flow as just one of the examples(maybe not the best example) ..but more of such "work" or "development" oriented benchmarks. Reply
  • pashhtk27 - Thursday, May 21, 2020 - link

    Or there should be proper support libraries for the integrated graphics to run tensor calculations. That would make GPU-less AI development machines a lot more cost effective. AMD and Intel are both working on this but it'll be hard to get around Nvidia's monopoly of AI computing. Free cloud compute services like colab have several problems and others are very cost prohibitive for students. And sometimes you just need to have a local system capable of loading and predicting. As a student, I think it would significantly lower the entry threshold if their cost effective laptops could run simple models and get output.

    We can talk about AI benchmarks then.
  • Gigaplex - Monday, May 18, 2020 - link

    As a developer I just use whatever my company gives me. I wouldn't be shopping for consumer CPUs for work purposes. Reply
  • wolfesteinabhi - Tuesday, May 19, 2020 - link

    not all developers are paid by their companies or make money with what they develop ... some are hobbyists and some do it as their "side" activities and with their own money at home apart from what they do at work with big guns!. Reply
  • mikato - Sunday, May 24, 2020 - link

    As a developer, I built my own new computer at work and got to pick everything within budget. Reply
  • Achaios - Monday, May 18, 2020 - link

    "Every so often there comes a processor that captures the market. "

    This used to be Sandy Bridge I5-2500K, all time best seller.

    Oh, how the Mighty Chipzilla has fallen.
  • mikelward - Monday, May 18, 2020 - link

    My current PC is a 2500K. My next one will be a 3600. Reply
  • Spunjji - Tuesday, May 19, 2020 - link

    Sandy was an absolute knockout. Most of the development thereafter was aimed at sticking similarly powerful CPUs in sleeker packages rather than increasing desktop performance, and while I feel like Intel deserve more credit for some things than they get (e.g. the leap in mobile power/performance that can from Haswell) they really shit the bed on 10nm and responding to Ryzen. Reply

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