ASUS Dual GeForce RTX 3070 in Crypto-Mining Ravencoin Hashrate (MH/s)

Here you can see how fast the ASUS Dual GeForce RTX 3070 is in Crypto-Mining Ravencoin Hashrate (MH/s). The performance of the graphics card in benchmarks or games primarily depends on the GPU architecture, the number of texture shaders and the memory size. The ASUS Dual GeForce RTX 3070 has 8 GB GDDR6 memory.
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GPU

Based on: NVIDIA GeForce RTX 3070
GPU Chip: GA104-300-A1 (Ampere)
Streaming Multiprocessors: 46
Shader: 5888
Raytracing Cores: 46

Memory

Memory Size: 8 GB
Memory Type: GDDR6
Memory Clock: 1.750 GHz
Memory bandwidth: 448 GB/s
Memory Interface: 256 bit

Benchmark results

Crypto-Mining Ravencoin Hashrate (MH/s)

KawPoW is a Proof-of-Work (PoW) algorithm and is calculated fastest with a modern graphics card. The hash rate values were determined under Hive OS with moderate overclocking.

KawPow Hashrate

ASUS Dual GeForce RTX 3070 ASUS Dual GeForce RTX 3070
8 GB GDDR6
29 MH/s
NVIDIA GeForce RTX 3070 NVIDIA GeForce RTX 3070
Average of gpu group
30 MH/s

KawPow Power consumption

ASUS Dual GeForce RTX 3070 ASUS Dual GeForce RTX 3070
8 GB GDDR6
173 W
NVIDIA GeForce RTX 3070 NVIDIA GeForce RTX 3070
Average of gpu group
170 W

KawPow Efficiency

ASUS Dual GeForce RTX 3070 ASUS Dual GeForce RTX 3070
8 GB GDDR6
0.17 MH/W
NVIDIA GeForce RTX 3070 NVIDIA GeForce RTX 3070
Average of gpu group
0.18 MH/W


More benchmarks for the graphics card
ASUS Dual GeForce RTX 3070

In order to determine the performance of a graphics card, so-called "benchmarks" are carried out. The benchmark software carries out special calculations to determine the performance of a graphics card. We use so-called theoretical or synthetic benchmarks (e.g. 3D Mark) as well as real game benchmarks. To ensure real comparability of the results, we pay attention to the correct execution of the benchmarks as well as the condition of the graphics card and the system.

We use the following benchmarks to measure the performance of a graphics card:


GPUs by group

Here we have listed more GPU groups for you:



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