NVIDIA GeForce RTX 3050 Ti Laptop (Mobile) - 70 W
Benchmark and Specs

NVIDIA GeForce RTX 3050 Ti Laptop (Mobile) - 70 W
GPU Memory
Based on: NVIDIA GeForce RTX 3050 Ti Laptop GPU (Mobile) Memory Size: 4 GB
GPU Chip: GA107 Memory Type: GDDR6
Execution units: 20 Memory Speed: 1.5 GHz
Shader: 2560 Memory Bandwith: 192 GB/s
Render Output Units: 48 Memory Interface: 128 bit
Texture Units: 80
Clock Speeds Thermal Design
Base Clock: 1.350 GHzDeviation vs GPU group+ 84 % TDP: 70 WDeviation vs GPU group+ 100 %
Boost Clock: 1.598 GHzDeviation vs GPU group+ 54 % TDP (up): 85 WDeviation vs GPU group+ 70 %
Avg (Game) Clock: Tjunction max: --
Overclocking: Yes PCIe-Power:
Cooler & Fans
Fan-Type: Radial Cooler-Type: Air cooling
Fan 1: -- Noise (Idle): 0 dB / Silent
Fan 2: -- Noise (Load): --
Connectivity Featureset
Max. Displays: 4 Max. resolution: 7680x4320
HDCP-Version: 2.3 DirectX: 12_2
HDMI Ports: -- Raytracing: Yes
DP Ports: 1x DP v1.4b DLSS / FSR: Yes
DVI Ports: --
VGA Ports: --
USB-C Ports: --
Supported Video Codecs
h264: Decode / Encode VP8: Decode
h265 / HEVC: Decode / Encode VP9: Decode
AV1: Decode
Dimensions Additional data
Length: -- GPU Interface: PCIe 4.0 x 16
Height: -- Release date: Q2/2021
Width: -- Release price: --
Width (Slots): -- Structure size: 8 nm
Weight: -- Part-no: --
Documents: data sheet


Benchmark results

FP32 Performance (Single-precision TFLOPS) - FP32 (TFLOPS)

The theoretical computing power of the graphics card with single precision (32 bit) in TFLOPS. TFLOPS indicates how many trillion FP32 floating point operations the graphics card (GPU) can perform per second. The larger this number, the faster the graphics card is.




Crypto-Mining Ethereum Hashrate (MH/s) - Ethash Hashrate

Ethash is the Proof-of-Work (PoW) algorithm used for the crypto currency Ethereum. Ethash is based on the Dagger-Hashimoto algorithm, but has been significantly changed in some places. For example, the memory requirement (GPU memory) was significantly increased in order to make it more difficult or even to prevent the calculation of the algorithm on so-called ASICs (Application Specific Integrated Circuits). Our benchmark results are based on a slight overclocking of the graphics card and the GPU memory. The hashrates were achieved under Hive OS with moderate overclocking settings.





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