AMD Opteron X3216 vs Google Tensor

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CPU comparison with benchmarks


AMD Opteron X3216 CPU1 vs CPU2 Google Tensor
AMD Opteron X3216 Google Tensor

CPU comparison

AMD Opteron X3216 or Google Tensor - which processor is faster? In this comparison we look at the differences and analyze which of these two CPUs is better. We compare the technical data and benchmark results.

The AMD Opteron X3216 has 2 cores with 2 threads and clocks with a maximum frequency of 3.00 GHz. Up to 32 GB of memory is supported in 2 memory channels. The AMD Opteron X3216 was released in Q2/2015.

The Google Tensor has 8 cores with 8 threads and clocks with a maximum frequency of 2.80 GHz. The CPU supports up to 12 GB of memory in 2 memory channels. The Google Tensor was released in Q4/2021.
AMD Opteron (4) Family Google Tensor (3)
AMD Opteron X3000 (3) CPU group Google Tensor (1)
0 Generation 1
Toronto (Excavator) Architecture G1
Desktop / Server Segment Mobile
-- Predecessor --
-- Successor Google Tensor G2

CPU Cores and Base Frequency

The AMD Opteron X3216 has 2 CPU cores and can calculate 2 threads in parallel. The clock frequency of the AMD Opteron X3216 is 1.60 GHz (3.00 GHz) while the Google Tensor has 8 CPU cores and 8 threads can calculate simultaneously. The clock frequency of the Google Tensor is at 2.80 GHz.

AMD Opteron X3216 Characteristic Google Tensor
2 Cores 8
2 Threads 8
normal Core architecture hybrid (Prime / big.LITTLE)
No Hyperthreading No
No Overclocking ? No
1.60 GHz (3.00 GHz) A-Core 2.80 GHz
2x Cortex-X1
-- B-Core 2.25 GHz
2x Cortex-A76
-- C-Core 1.80 GHz
4x Cortex-A55

NPU AI performance

The performance values of the processor's AI unit. The isolated NPU performance is specified here, the total AI performance (NPU+CPU+iGPU) can be higher. Processors with support for artificial intelligence (AI) and machine learning (ML) can process many calculations, especially audio, image and video processing, much faster than classic processors.

AMD Opteron X3216 Characteristic Google Tensor
-- AI hardware Google Tensor AI
-- AI specifications Google Edge TPU @ 1.6 TOPS
-- NPU + CPU + iGPU --

Integrated graphics (iGPU)

The AMD Opteron X3216 or Google Tensor has integrated graphics, called iGPU for short. The iGPU uses the system's main memory as graphics memory and sits on the processor's die.

AMD Radeon R7 - 256 (Toronto) GPU ARM Mali-G78 MP20
0.80 GHz GPU frequency 0.76 GHz
-- GPU (Turbo) --
0 GPU Generation Vallhall 2
Technology 5 nm
3 Max. displays 1
4 Compute units 20
256 Shader 320
No Hardware Raytracing No
No Frame Generation No
-- Max. GPU Memory --
12 DirectX Version 12

Hardware codec support

A photo or video codec that is accelerated in hardware can greatly accelerate the working speed of a processor and extend the battery life of notebooks or smartphones when playing videos.

AMD Radeon R7 - 256 (Toronto) GPU ARM Mali-G78 MP20
Decode Codec h265 / HEVC (8 bit) Decode / Encode
No Codec h265 / HEVC (10 bit) Decode / Encode
Decode / Encode Codec h264 Decode / Encode
No Codec VP9 Decode / Encode
No Codec VP8 Decode / Encode
No Codec AV1 Decode
No Codec AVC Decode / Encode
No Codec VC-1 Decode / Encode
Decode Codec JPEG Decode / Encode

Memory & PCIe

The AMD Opteron X3216 can use up to 32 GB of memory in 2 memory channels. The maximum memory bandwidth is 25.6 GB/s. The Google Tensor supports up to 12 GB of memory in 2 memory channels and achieves a memory bandwidth of up to 53.0 GB/s.

AMD Opteron X3216 Characteristic Google Tensor
DDR4-1600 Memory LPDDR5-5500
32 GB Max. Memory 12 GB
2 (Dual Channel) Memory channels 2 (Dual Channel)
25.6 GB/s Max. Bandwidth 53.0 GB/s
Yes ECC No
1.00 MB L2 Cache 8.00 MB
-- L3 Cache --
3.0 PCIe version --
8 PCIe lanes --
7.9 GB/s PCIe Bandwidth --

Thermal Management

The thermal design power (TDP for short) of the AMD Opteron X3216 is 15 W, while the Google Tensor has a TDP of 10 W. The TDP specifies the necessary cooling solution that is required to cool the processor sufficiently.

AMD Opteron X3216 Characteristic Google Tensor
15 W TDP (PL1 / PBP) 10 W
-- TDP (PL2) --
-- TDP up --
12 W TDP down --
-- Tjunction max. --

Technical details

The AMD Opteron X3216 is manufactured in 28 nm and has 1.00 MB cache. The Google Tensor is manufactured in 5 nm and has a 8.00 MB cache.

AMD Opteron X3216 Characteristic Google Tensor
28 nm Technology 5 nm
Unknown Chip design Unknown
x86-64 (64 bit) Instruction set (ISA) Armv8-A (64 bit)
SSE4a, SSE4.1, SSE4.2, AVX2 ISA extensions --
FP4 Socket --
AMD-V, AMD-Vt Virtualization None
Yes AES-NI No
Windows 10, Linux Operating systems Android
Q2/2015 Release date Q4/2021
-- Release price --
show more data show more data


Rate these processors

Here you can rate the AMD Opteron X3216 to help other visitors make their purchasing decisions. The average rating is 0 stars (0 ratings). Rate now:
Here you can rate the Google Tensor to help other visitors make their purchasing decisions. The average rating is 4.3 stars (14 ratings). Rate now:


Average performance in benchmarks

⌀ Single core performance in 2 CPU benchmarks
AMD Opteron X3216 (40%)
Google Tensor (100%)
⌀ Multi core performance in 2 CPU benchmarks
AMD Opteron X3216 (24%)
Google Tensor (100%)

Geekbench 5, 64bit (Single-Core)

Geekbench 5 is a cross plattform benchmark that heavily uses the systems memory. A fast memory will push the result a lot. The single-core test only uses one CPU core, the amount of cores or hyperthreading ability doesn't count.
AMD Opteron X3216 AMD Opteron X3216
2C 2T @ 3.00 GHz
456 (44%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
1043 (100%)

Geekbench 5, 64bit (Multi-Core)

Geekbench 5 is a cross plattform benchmark that heavily uses the systems memory. A fast memory will push the result a lot. The multi-core test involves all CPU cores and taks a big advantage of hyperthreading.
AMD Opteron X3216 AMD Opteron X3216
2C 2T @ 1.60 GHz
751 (26%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
2915 (100%)

Geekbench 6 (Single-Core)

Geekbench 6 is a benchmark for modern computers, notebooks and smartphones. What is new is an optimized utilization of newer CPU architectures, e.g. based on the big.LITTLE concept and combining CPU cores of different sizes. The single-core benchmark only evaluates the performance of the fastest CPU core, the number of CPU cores in a processor is irrelevant here.
AMD Opteron X3216 AMD Opteron X3216
2C 2T @ 3.00 GHz
533 (36%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
1494 (100%)

Geekbench 6 (Multi-Core)

Geekbench 6 is a benchmark for modern computers, notebooks and smartphones. What is new is an optimized utilization of newer CPU architectures, e.g. based on the big.LITTLE concept and combining CPU cores of different sizes. The multi-core benchmark evaluates the performance of all of the processor's CPU cores. Virtual thread improvements such as AMD SMT or Intel's Hyper-Threading have a positive impact on the benchmark result.
AMD Opteron X3216 AMD Opteron X3216
2C 2T @ 1.60 GHz
764 (21%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
3639 (100%)

iGPU - FP32 Performance (Single-precision GFLOPS)

The theoretical computing performance of the internal graphics unit of the processor with simple accuracy (32 bit) in GFLOPS. GFLOPS indicates how many billion floating point operations the iGPU can perform per second.
AMD Opteron X3216 AMD Opteron X3216
AMD Radeon R7 - 256 (Toronto) @ 0.80 GHz
410 (21%)
Google Tensor Google Tensor
ARM Mali-G78 MP20 @ 0.76 GHz
1943 (100%)

AnTuTu 9 Benchmark

The AnTuTu 9 benchmark is very well suited to measuring the performance of a smartphone. AnTuTu 9 is quite heavy on 3D graphics and can now also use the "Metal" graphics interface. In AnTuTu, memory and UX (user experience) are also tested by simulating browser and app usage. AnTuTu version 9 can compare any ARM CPU running on Android or iOS. Devices may not be directly comparable when benchmarked on different operating systems.

In the AnTuTu 9 benchmark, the single-core performance of a processor is only slightly weighted. The rating is made up of the multi-core performance of the processor, the speed of the working memory, and the performance of the internal graphics.
AMD Opteron X3216 AMD Opteron X3216
2C 2T @ 1.60 GHz
0 (0%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
691770 (100%)

AnTuTu 8 Benchmark

The AnTuTu 8 Benchmark measures the performance of a SoC. AnTuTu benchmarks the CPU, GPU, Memory as well as the UX (User Experience) by simulating browser and app usage. AnTuTu can benchmark any ARM CPU that runs under Android or iOS. Devices may not be directly compareable if the benchmark has been performed under different operating systems.

In the AnTuTu 8 benchmark, the single-core performance of a processor is only slightly weighted. The evaluation consists of the multi-core performance of the processor, the speed of the RAM and the performance of the internal graphics.
AMD Opteron X3216 AMD Opteron X3216
2C 2T @ 1.60 GHz
0 (0%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
612494 (100%)

Estimated results for PassMark CPU Mark

Some of the CPUs listed below have been benchmarked by CPU-monkey. However the majority of CPUs have not been tested and the results have been estimated by a CPU-monkey’s secret proprietary formula. As such they do not accurately reflect the actual Passmark CPU mark values and are not endorsed by PassMark Software Pty Ltd.
AMD Opteron X3216 AMD Opteron X3216
2C 2T @ 1.60 GHz
1475 (100%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
0 (0%)

AI performance (NPU)

The performance values of the processor's AI unit. The isolated NPU performance is given here, the total AI performance (NPU+CPU+iGPU) can be higher.

Processors with the support of artificial intelligence (AI) and machine learning (ML) can process many calculations, especially audio, image and video processing, much faster than classic processors. The performance is given in the number (trillions) of arithmetic operations per second (TOPS).
AMD Opteron X3216 AMD Opteron X3216
2C 2T @ 1.60 GHz
0 (0%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
1.6 (100%)

Devices using this processor

AMD Opteron X3216 Google Tensor
Unknown Google Pixel 6
Google Pixel 6 Pro

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