ASUS Dual series GeForce GTX 1060 OC edition 3GB vs. ASUS Phoenix GeForce GTX 1650 SUPER

GPU comparison with benchmarks

ASUS Dual series GeForce GTX 1060 OC edition 3GB
-VS-
ASUS Phoenix GeForce GTX 1650 SUPER
GPU
NVIDIA GeForce GTX 1060 3GB Based on NVIDIA GeForce GTX 1650 SUPER
GP106-300-A1 GPU Chip TU116-250-KA-A1
9 Execution units 20
1152 Shader 1280
48 Render Output Units 32
72 Texture Units 80
Memory
3 GB Memory Size 4 GB
GDDR5 Memory Type GDDR6
2.002 GHz Memory Speed 1.5 GHz
192 GB/s Memory Bandwith 192 GB/s
192 bit Memory Interface 128 bit
Clock Speeds
1.569 GHz Base Clock 1.530 GHz
1.809 GHz Boost Clock 1.755 GHz
1.79 GHz Avg (Game) Clock 1.73 GHz
Yes Overclocking Yes
Thermal Design
120 W TDP 100 W
-- TDP (up) --
-- Tjunction max --
1 x 6-Pin PCIe-Power 1 x 6-Pin
Cooler & Fans
Axial Fan-Type Axial
2 x 90 mm Fan 1 1 x 100 mm
-- Fan 2 --
Air cooling Cooler-Type Air cooling
0 dB / Silent Noise (Idle) 0 dB / Silent
-- Noise (Load) --
Connectivity
4 Max. Displays 3
2.2 HDCP-Version 2.2
2x HDMI v2.0b HDMI Ports 1x HDMI v2.0b
2x DP v1.4 DP Ports 1x DP v1.4
1 DVI Ports 1
-- VGA Ports --
-- USB-C Ports --
Featureset
7680x4320 Max. resolution 3840x2160
12_1 DirectX 12_1
No Raytracing No
No DLSS / FSR No
Supported Video Codecs
Decode / Encode h264 Decode / Encode
Decode / Encode h265 / HEVC Decode / Encode
No AV1 No
No VP8 Decode
Decode VP9 Decode
Dimensions
242 mm Length 174 mm
130 mm Height 121 mm
43 mm Width 39 mm
2 PCIe-Slots Width (Slots) 2 PCIe-Slots
-- Weight --
PCIe 3.0 x 16 GPU Interface PCIe 3.0 x 16
Additional data
DUAL-GTX1060-O3G Part-no PH-GTX1650S-4G
Q3/2016 Release date Q4/2019
-- Release price --
16 nm Structure size 12 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 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.




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