Unisoc Tanggula T740 5G vs Unisoc Tiger T618
The Unisoc Tiger T618 and the Unisoc Tanggula T740 5G are two processors that differ in their specifications.
Starting with the Unisoc Tiger T618, it is equipped with an architecture that consists of 2x 2.0 GHz Cortex-A75 cores and 6x 2.0 GHz Cortex-A55 cores. This processor has a total of 8 cores and operates on the ARMv8.2-A instruction set. With a 12 nm lithography and a TDP of 10 watts, the Tiger T618 is designed to deliver efficient performance while minimizing power consumption. Additionally, it features a Neural Processing Unit (NPU) for specialized AI computing.
On the other hand, the Unisoc Tanggula T740 5G also houses 8 cores, but with a different architecture. It is built with 4x 1.8 GHz Cortex-A75 cores and 4x 1.8 GHz Cortex-A55 cores. Similar to the Tiger T618, it operates on the ARMv8.2-A instruction set and has a 12 nm lithography. However, the Tanggula T740 5G stands out with its Dual NPU, which enhances its neural processing capabilities.
When comparing these two processors, it is evident that they have some similarities in terms of their lithography and instruction set. However, they differ in their CPU cores and architecture as well as their neural processing setups.
The Tiger T618 offers a higher clock speed with its 2.0 GHz Cortex-A75 cores, which could potentially result in better overall performance. It also has more Cortex-A55 cores, which can handle tasks that require lower power consumption. Meanwhile, the Tanggula T740 5G has a balanced distribution of Cortex-A75 and Cortex-A55 cores, focusing on delivering equilibrium in terms of processing power and energy efficiency.
In terms of neural processing, the Tiger T618 is equipped with a single NPU, while the Tanggula T740 5G boasts dual NPUs. This indicates that the Tanggula T740 5G may be more capable of efficiently handling AI-related tasks due to its enhanced neural processing setup.
In conclusion, the Unisoc Tiger T618 and Unisoc Tanggula T740 5G processors differ in their CPU cores, architecture, and neural processing capabilities. While the Tiger T618 offers higher clock speeds and a single NPU, the Tanggula T740 5G provides a balanced distribution of cores and dual NPUs. The choice between these processors would depend on the specific requirements of the target device and the intended usage scenarios.
Starting with the Unisoc Tiger T618, it is equipped with an architecture that consists of 2x 2.0 GHz Cortex-A75 cores and 6x 2.0 GHz Cortex-A55 cores. This processor has a total of 8 cores and operates on the ARMv8.2-A instruction set. With a 12 nm lithography and a TDP of 10 watts, the Tiger T618 is designed to deliver efficient performance while minimizing power consumption. Additionally, it features a Neural Processing Unit (NPU) for specialized AI computing.
On the other hand, the Unisoc Tanggula T740 5G also houses 8 cores, but with a different architecture. It is built with 4x 1.8 GHz Cortex-A75 cores and 4x 1.8 GHz Cortex-A55 cores. Similar to the Tiger T618, it operates on the ARMv8.2-A instruction set and has a 12 nm lithography. However, the Tanggula T740 5G stands out with its Dual NPU, which enhances its neural processing capabilities.
When comparing these two processors, it is evident that they have some similarities in terms of their lithography and instruction set. However, they differ in their CPU cores and architecture as well as their neural processing setups.
The Tiger T618 offers a higher clock speed with its 2.0 GHz Cortex-A75 cores, which could potentially result in better overall performance. It also has more Cortex-A55 cores, which can handle tasks that require lower power consumption. Meanwhile, the Tanggula T740 5G has a balanced distribution of Cortex-A75 and Cortex-A55 cores, focusing on delivering equilibrium in terms of processing power and energy efficiency.
In terms of neural processing, the Tiger T618 is equipped with a single NPU, while the Tanggula T740 5G boasts dual NPUs. This indicates that the Tanggula T740 5G may be more capable of efficiently handling AI-related tasks due to its enhanced neural processing setup.
In conclusion, the Unisoc Tiger T618 and Unisoc Tanggula T740 5G processors differ in their CPU cores, architecture, and neural processing capabilities. While the Tiger T618 offers higher clock speeds and a single NPU, the Tanggula T740 5G provides a balanced distribution of cores and dual NPUs. The choice between these processors would depend on the specific requirements of the target device and the intended usage scenarios.
AnTuTu 10
Total Score
GeekBench 6 Single-Core
Score
GeekBench 6 Multi-Core
Score
CPU cores and architecture
Architecture | 4x 1.8 GHz – Cortex-A75 4x 1.8 GHz – Cortex-A55 |
2x 2.0 GHz – Cortex-A75 6x 2.0 GHz – Cortex-A55 |
Number of cores | 8 | 8 |
Instruction Set | ARMv8.2-A | ARMv8.2-A |
Lithography | 12 nm | 12 nm |
TDP | 10 Watt | |
Neural Processing | Dual NPU | NPU |
Memory (RAM)
Max amount | up to 8 GB | up to 6 GB |
Memory type | LPDDR4X | LPDDR4X |
Memory frequency | 1866 MHz | 1866 MHz |
Memory-bus | 2x16 bit |
Storage
Storage specification | UFS 2.1 | eMMC 5.1 |
Graphics
GPU name | Imagination PowerVR GM9446 | Mali-G52 MP2 |
GPU Architecture | PowerVR Rogue | Mali Bifrost |
GPU frequency | 800 MHz | 850 MHz |
Execution units | 2 | |
Shaders | 32 | |
DirectX | 11 | |
OpenCL API | 4.0 | 2.1 |
OpenGL API | ES 3.2 | ES 3.2 |
Vulkan API | 1.1 | 1.2 |
Camera, Video, Display
Max screen resolution | 2960x1440@60Hz | 2400x1080 |
Max camera resolution | 1x 64MP | 1x 64M |
Max Video Capture | 4K@30fps | FullHD@60fps |
Video codec support | H.264 (AVC) H.265 (HEVC) VP8 VP9 |
H.264 (AVC) H.265 (HEVC) |
Wireless
4G network | Yes | Yes |
5G network | Yes | Yes |
Peak Download Speed | 1.5 Gbps | 0.3 Gbps |
Peak Upload Speed | 0.75 Gbps | 0.1 Gbps |
Wi-Fi | 5 (802.11ac) | 5 (802.11ac) |
Bluetooth | 5.0 | 5.0 |
Satellite navigation | BeiDou GPS Galileo GLONASS |
BeiDou GPS Galileo GLONASS |
Supplemental Information
Launch Date | 2020 Quarter 1 | 2019 August |
Partnumber | T740, Tiger T7510 | T618 |
Vertical Segment | Mobiles | Mobiles |
Positioning | Mid-end | Mid-end |
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