Etchash
Ethash family3 bányászható érme · mértékegység: MH/s · proof of work
A(z) Etchash bemutatása
Ethereum Classic's variant of Ethash with a slower-growing DAG, adopted after the ETC network reduced its DAG size to keep 4 GB GPUs mining. Behaviour is otherwise identical to Ethash.
Typical hardware: ASIC/GPUMemory-hardSince 2020
Érmék a(z) Etchash algoritmuson
Hardverek a(z) Etchash algoritmushoz
| Hardver | Típus | Hashrate | Fogyasztás |
|---|---|---|---|
| ASIC | 23.4 GH/s | 2550 W | |
| ASIC | 15.5 GH/s | 3100 W | |
| ASIC | 15.5 GH/s | 3100 W | |
| ASIC | 12.5 GH/s | 2300 W | |
| ASIC | 12.5 GH/s | 2300 W | |
| ASIC | 10 GH/s | 1500 W | |
| ASIC | 10 GH/s | 1500 W | |
| ASIC | 9.5 GH/s | 2470 W | |
| ASIC | 9 GH/s | 2340 W | |
| ASIC | 9 GH/s | 2340 W | |
| ASIC | 9 GH/s | 2340 W | |
| ASIC | 5.8 GH/s | 1900 W | |
| ASIC | 5.8 GH/s | 1900 W | |
| ASIC | 5.25 GH/s | 1900 W | |
| FForestMiner EPU XC | ASIC | 4.25 GH/s | 3315 W |
| ASIC | 3.8 GH/s | 760 W | |
| ASIC | 3.8 GH/s | 760 W | |
| ASIC | 3.78 GH/s | 2260 W | |
| ASIC | 3.78 GH/s | 2260 W | |
| ASIC | 3.68 GH/s | 2200 W | |
| ASIC | 3.6 GH/s | 3100 W | |
| ASIC | 3.4 GH/s | 475 W | |
| ASIC | 3.4 GH/s | 475 W | |
| ASIC | 2.5 GH/s | 1200 W | |
| ASIC | 2.5 GH/s | 1200 W | |
| ASIC | 2.4 GH/s | 1920 W | |
| ASIC | 2.4 GH/s | 1920 W | |
| ASIC | 2.4 GH/s | 1920 W | |
| ASIC | 2.05 GH/s | 520 W | |
| ASIC | 2.05 GH/s | 520 W | |
| ASIC | 1.95 GH/s | 620 W | |
| ASIC | 1.95 GH/s | 630 W | |
| ASIC | 1.75 GH/s | 550 W | |
| ASIC | 1.65 GH/s | 550 W | |
| ASIC | 1.55 GH/s | 1240 W | |
| ASIC | 1.55 GH/s | 1240 W | |
| ASIC | 1.5 GH/s | 2350 W | |
| ASIC | 1.5 GH/s | 2500 W | |
| ASIC | 1.5 GH/s | 2500 W | |
| ASIC | 1.2 GH/s | 165 W | |
| ASIC | 1.2 GH/s | 165 W | |
| ASIC | 1.04 GH/s | 480 W | |
| ASIC | 1.04 GH/s | 370 W | |
| ASIC | 1.04 GH/s | 370 W | |
| ASIC | 950 MH/s | 750 W | |
| ASIC | 900 MH/s | 365 W | |
| ASIC | 850 MH/s | 690 W | |
| ASIC | 840 MH/s | 380 W | |
| ASIC | 840 MH/s | 340 W | |
| ASIC | 750 MH/s | 1350 W |
Katalógus frissítve 3 d agoMethodology