Evernode (EVR) 挖矿
可用算法： EvrProgPow · 全网算力 919 MH/s
可信度 75/100 High confidence
为什么是这个分数？
- Freshness100
- Market data60
- Network data100
- Pool coverage0
- Source coverage100
- Identity67
价格
$0.0000071▼ 16%
市值
$71,244▼ 16%
24小时成交量
$21
难度
12.62▲ 12%
全网算力
919 MH/s▲ 14%
区块奖励
1.25k EVR
出块时间
59s
最新高度
2031714
Aug 21Sep 19Sep 20
Aug 21Sep 19Sep 20
Aug 21Sep 19Sep 20
Aug 21Sep 19Sep 20
EVR 挖矿计算器
使用您的算力挖掘 EVR 的预估收益、成本和利润。
| 周期 | 预估奖励 | 预估收入 | 成本 | 预估利润 |
|---|---|---|---|---|
| 每小时 | 8300.2267 EVR | $0.05890.00000073 BTC | $0 | $0.0589 |
| 每天 | 199205.4419 EVR | $1.41390.00001743 BTC | $0 | $1.4139 |
| 每周 | 1394438.0935 EVR | $9.89740.00012198 BTC | $0 | $9.8974 |
| 每月 | 5976163.2580 EVR | $42.420.00052277 BTC | $0 | $42.42 |
EVR 最佳硬件
按 $0.08/kWh 基准计算利润，可在计算器中调整。
| 矿机 | 日收入 | 日利润 | 评分 | 风险 |
|---|---|---|---|---|
 Nvidia GeForce RTX 4090 | $0.95 | $0.32 | 40/100 | |
| Nvidia CMP 170HX | $0.53 | $0.24 | 40/100 | |
 AMD RX 7900 XTX | $0.79 | $0.21 | 40/100 | |
| Nvidia RTX 4080 | $0.68 | $0.21 | 40/100 | |
| Nvidia GeForce RTX 4080 | $0.67 | $0.19 | 40/100 | |
| Nvidia RTX 3080 | $0.79 | $0.18 | 40/100 | |
| Nvidia RTX 4070Ti | $0.60 | $0.16 | 40/100 | |
| Nvidia GeForce RTX 4080 Super | $0.69 | $0.16 | 40/100 | |
| AMD RX 7900 XT | $0.65 | $0.15 | 40/100 | |
| Nvidia RTX 3080Ti | $0.82 | $0.15 | 40/100 |
关于 Evernode 的常见问题
How long does it take to mine 1 EVR?
At the current Evernode difficulty it would take about 1 hours with Nvidia GeForce RTX 4090.
What is the current Evernode difficulty?
Evernode network difficulty is currently 12.62.
What is the current Evernode network hashrate?
Evernode network hashrate is currently 919 MH/s.
Which hardware can mine Evernode?
Evernode runs on the EvrProgPow algorithm: the strongest listed devices today are Nvidia GeForce RTX 4090 (GPU). See the full ranking in the hardware table above.
Is Evernode worth mining?
With Nvidia GeForce RTX 4090, mining EVR stays profitable as long as your electricity costs less than $0.12 per kWh. Run your own numbers in the calculator above.
网络数据更新于 3 min agoMethodology