Finding the best CPU for machine learning makes all the difference in the speed and quality of your programming. Because of that, we are bringing to you the top-rated processors you can get for any branch of this area. If you are looking for the best deep learning processors and want to see them compared to pick the one for you, just keep reading.
Are short on time and just want to know what are the best CPUs for machine learning on the market in 2024? Alright, then the top rated processor for that is the highly rated AMD Ryzen Threadripper 3970X Desktop Processor. If you’re looking for a more pocket friendly option, go for the AMD Ryzen 9 3900X CPU.
Best CPU for Deep Learning: Quick Comparison
BEST RATED  |
AMD Ryzen Threadripper 3970X
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RUNNER UP  |
AMD Ryzen 9 3900X
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Intel Core i9-11900K
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Intel Core i9-9900K
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AMD Ryzen 7 3800X
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AMD Ryzen 5 3600
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Best CPU for Machine Learning 2024: Reviews
1. AMD Ryzen Threadripper 3970X Desktop Processor
Best AMD Processor for Machine Learning
We know some people may find this price out of their budget but this is the best option for those who can afford it and you won’t want anything else in 2024.
This CPU is manufactured with 7nm FinFET transistors with silicon wafers created by TSMC.
The advantage of 7nm is evident: higher density of transistors in the same space, the possibility of introducing more functional units, and greater energy efficiency.
This CPU has 32 cores and 64 processing threads, thus being the processor with the highest raw power for desktop computers.
This large number of cores can operate at a base frequency of 3.7 GHz, with the possibility of a maximum frequency of up to 4.5 GHz in single-core overclocking.
Cache memory counts with 144 MB divided into 128 MB of L3 cache, 16 MB of L2 cache, and also 3 MB of L1 cache, divided as always into L1I and L1D cache. All of this brings the CPU’s TDP up to 280W.
As in the previous generation, the maximum admissible temperature is 68ºC. Finally, it natively supports up to 256 GB of DDR4 RAM at 3200 MHz in Quad Channel.
Pros
- A unique performance in the market
- Excellent multi-thread performance
- Easy to overclock
- Indium solder
Cons
- Not for everyone’s pockets
2. AMD Ryzen 9 3900X Desktop Processor
Best CPU For Data Science
These physical cores are built by TSMC in 7nm FinFET lithography and can reach a frequency of 3.8 GHz in base mode and 4.6 GHz in boost mode.
In fact, this processor comes with improved AMD Precision Boost 2 technology that will increase the frequency of the cores only when necessary, requesting information about the load every 1 ms.
For cache memory, a total of 64MB of L3 cache along with 6MB of L2 cache, 512KB for each core.
Moreover, the native support for the PCI-Express 4.0 bus has been implemented, teaming with the AMD X570 chipset to support faster graphics cards in the near future.
The processor TDP remains at only 105W despite having 12 cores, being one of the advantages of the 7 nm: less consumption and more power.
The 12nm memory controller on this CPU supports 128GB 3200MHz DDR4 in the dual-channel configuration.
This is the best model for machine learning you will find which is in the price range you might be expecting in 2024.
Pros
- 12 cores
- Overclocking makes this processor even more impressive
- Better than Intel in the same price range
Cons
- Compatible motherboards that allow PCIe 4.0 support are too expensive
3. Intel Core i9-11900K Processor
Best Intel CPU For AI Programming
The 11900K represents the highest level of Intel Rocket Lake S desktop architecture, which uses a 14 +++ nm transistor manufacturing process.
For cores, this model maintains the already classic 8 cores/16 threads of the i9 models.
The IPC has undergone a substantial improvement, and in mono-core tasks, it has an increase of more than 15%, which is a lot.
This way, it intends to get close to the performance provided by AMD’s Zen3 architecture, reaching 630 points in Cinebench R20 for example.
This CPU has a base frequency of 3.5 GHz. Overall, the boost frequency in all cores simultaneously will be 4.7 GHz.
But depending on the motherboard, it can go up to 4.8 GHz as it happens in the Asus ROG Maximus XIII Hero.
Thanks to the Turbo Boost 2.0 function, it can reach 5.1 GHz in a single core. With the Turbo Boost Max 3.0 mode, 5.2 GHz. And with the Thermal Velocity Boost mode, it will reach a maximum of 5.3 GHz.
Pros
- Amazing overclocking features
- Compatible with older Z490 motherboards
- Support for PCIe 4.0
Cons
- Power-hungry
- Gets very hot
4. Intel Core i9-9900K Desktop Processo
Best Budget CPU For Machine Learning
However, this is one of the best cost benefits you can get if you are looking for a good CPU for machine learning. It is cheaper than the options already presented so far but delivers great results.
Intel Core i9-9900K comes with an 8-core and 16-thread configuration, with a base frequency of 3.6 GHz, and a maximum turbo frequency of 5 GHz.
It features a 16 MB L3 cache and a TDP of only 95W, very tight for a processor like this.
It also includes a dual-channel DDR4 2666 memory controller that supports a maximum of 64GB, more than enough for most users’ purposes.
This memory controller is capable of offering a bandwidth of 41.6 GB/s.
Pros
- More cores than the previous Intel Core series
- A beast for multi-threaded operations
- Unlocked multiplier
Cons
- Gets very hot
5. AMD Ryzen 7 3800X CPU Processor
Cheap AMD CPU For Machine Learning
The Ryzen 7 3800X presents 8 cores and 16 processing threads.
7nm FinFET transistors manufactured by TSMC have been used in its construction, which are the ones that make up the Zen 2 architecture.
And like all other Ryzen CPUs, this one also has AMD SMT multi-thread technology and the unlocked multiplier and with overclocking capacity.
The cores are able to reach a speed of 3.9 GHz at their base frequency, and 4.5 GHz at their theoretical maximum frequency.
All this is possible thanks to AMD Precision Boost Overdrive technology that manages the CPU voltage to increase the frequency only when necessary.
It is important to keep in mind that these processors are based on chiplets, which are basically 8-core modules with cache memory (CCX) in which the manufacturer deactivates or activates the operating cores of each model.
In this 3800X, 4 cores belong to CCX1 and another 4 to CCX2, thus distributing the activity.
Pros
- Very solid performance
- Great cheap alternative for machine learning
- PCIe 4.0 support
Cons
- PCIe 4.0 requires an X570 mobo
6. AMD Ryzen 5 3600 CPU Processor
Alternative CPU For Machine Learning
It is responsible for communication with the RAM, and this model saw a huge impact on Zen architecture.
This allowed a decrease in latency and an increase in maximum capacity with up to 128 GB in Dual Channel at 3200 MHz.
This CPU counts with 6 cores and 12 processing threads, thanks to AMD SMT multithreading technology, analogous to Intel’s Hyperthreading. They offer a speed of 3.6 GHz base frequency and 4.2 GHz in turbo mode.
This very powerful CPU has a TDP of only 65W, which is great.
The chiplet architecture already mentioned for other AMD models is present here too. Each AMD chiplet has 8 cores and 32 cache memory.
Even at a low price, this AMD model is a beast and can help many data scientists with machine learning or other related operations in 2024.
Pros
- Great price
- Better than an Intel Core i5-9600K for applications
- Its power is close to 8700K and 9700K
Cons
- Not better than Intel for gaming
Deep Learning Processor FAQ
Which CPU Is Best for Machine Learning?
One of the very best CPUs for that is the AMD Ryzen Threadripper 3970X. It has a high price in comparison to even other processors in this article, but it is because of its elevated power.
Which Processor Is Best for AI Programming?
AI Programming is in fact the umbrella term in which machine learning fits. That being the case, the recommended AMD processor from above is the best option for all AI programming scenarios. If you are looking for something else, though, you can go with the AMD Ryzen 9 3900X.
Is AMD Good for Machine Learning?
Yes. In fact, some of AMD’s CPUs are among the best models you can buy for machine learning. The Threadripper series, for example, presents CPUs with up to 64 cores, which is a blast for intensive activities like this.
Even other models which are not that expensive or include so many cores are excellent options for such a task.
Is i9 9900K Good for Machine Learning?
Yes, it certainly is. Many professionals use this i9 model for machine learning and other similarly intensive activities. Even though it doesn’t have the number of cores that AMD Threadripper can boast about, it counts with 8 cores/16 threads that can work up to 5.0GHz.
Final Words About the Best CPU for Deep Learning
As of now, there are many options in the market if you are looking for the best CPU for machine learning. We compared them briefly, and we reached the conclusion that the best you can get for deep learning is the AMD Ryzen Threadripper 3970X.
That model has a very high price which some people might not want to pay. Because of that, right behind its performance, we can recommend the top-rated processors AMD Ryzen 9 3900X and Intel Core i9-11900K.
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