ASUS Dual GeForce GTX 1660 Advanced EVO vs. NVIDIA GeForce RTX 3050 Ti Laptop (Mobile) - 80 W

GPU comparison with benchmarks

ASUS Dual GeForce GTX 1660 Advanced EVO
-VS-
NVIDIA GeForce RTX 3050 Ti Laptop (Mobile) - 80 W
GPU
NVIDIA GeForce GTX 1660 Based on NVIDIA GeForce RTX 3050 Ti Laptop GPU (Mobile)
TU116-300-A1 GPU Chip GA107
22 Execution units 20
1408 Shader 2560
48 Render Output Units 48
88 Texture Units 80
Memory
6 GB Memory Size 4 GB
GDDR5 Memory Type GDDR6
2 GHz Memory Speed 1.5 GHz
192 GB/s Memory Bandwith 192 GB/s
192 bit Memory Interface 128 bit
Clock Speeds
1.530 GHz Base Clock 1.462 GHz
1.830 GHz Boost Clock 1.695 GHz
1.80 GHz Avg (Game) Clock
Yes Overclocking Yes
Thermal Design
120 W TDP 80 W
-- TDP (up) 95 W
-- Tjunction max --
1 x 8-Pin PCIe-Power
Cooler & Fans
Axial Fan-Type Radial
2 x 90 mm Fan 1 --
-- Fan 2 --
Air cooling Cooler-Type Air cooling
0 dB / Silent Noise (Idle) 0 dB / Silent
-- Noise (Load) --
Connectivity
3 Max. Displays 4
2.2 HDCP-Version 2.3
1x HDMI v2.0b HDMI Ports --
1x DP v1.4 DP Ports 1x DP v1.4b
1 DVI Ports --
-- VGA Ports --
-- USB-C Ports --
Featureset
3840x2160 Max. resolution 7680x4320
12_1 DirectX 12_2
No Raytracing Yes
No DLSS / FSR Yes
Supported Video Codecs
Decode / Encode h264 Decode / Encode
Decode / Encode h265 / HEVC Decode / Encode
No AV1 Decode
Decode VP8 Decode
Decode VP9 Decode
Dimensions
242 mm Length --
130 mm Height --
53 mm Width --
3 PCIe-Slots Width (Slots) --
-- Weight --
PCIe 3.0 x 16 GPU Interface PCIe 4.0 x 16
Additional data
DUAL-GTX1660-A6G-EVO Part-no --
Q1/2019 Release date Q2/2021
-- Release price --
12 nm Structure size 8 nm
data sheet 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.




Crypto-Mining Ergo Hashrate (MH/s) - Autolykos 2 Hashrate

The crypto currency Ergo is based on the Autolykos algorithm, which was updated in version 2 (Autolykos 2) in early 2021. The Autolykos 2 algorithm is based on the PoW concept and can be efficiently calculated by a graphics card. When calculating Ergo Coins, ASICs have no efficiency advantage over modern graphics cards, which should make Ergo attractive for as many miners as possible. The Ergo protocol is based on the blockchain and has been optimized for a very long shelf life. The hashrates were achieved under Hive OS with moderate overclocking settings.




Crypto-Mining Ravencoin Hashrate (MH/s) - KawPow Hashrate

The KawPoW algorithm has been used with the crypto currency Ravencoin since May 2020. Previously, Ravencoin used ProgPoW (X16R and X16Rv2). KawPoW is a Proof-of-Work (PoW) algorithm and is calculated the fastest with a modern graphics card. KawPoW is based on a changing algorithm (X15 and SHA51) and can therefore not be calculated via ASIC. The developers want to protect Ravencoin from large mining farms that often use ASICs. In addition to Ravencoin, other cryptocurrencies are based on KawPoW, including Hilux and Gravium. The hashrates were achieved under Hive OS with moderate overclocking settings.




Crypto-Mining Vertcoin Hashrate (MH/s) - Verthash Hashrate

The crypto currency VertCoin (VTC) is calculated with the new Verthash algorithm since January 2021. This is a very memory-intensive PoW algorithm that is difficult to calculate with an ASIC. The developers have set themselves the goal that VertCoin should be calculated via a graphics card and not with so-called ASICs. These are increasingly used in large mining farms. Verthash currently requires a graphics card with at least 2 GB of memory. The hashrates were achieved under Hive OS with moderate overclocking settings.




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