Iron Fish (IRON) 挖矿
可用算法: FishHash · 全网算力 282.1 GH/s
可信度 75/100 High confidence
为什么是这个分数?
- Freshness100
- Market data60
- Network data100
- Pool coverage100
- Source coverage100
- Identity0
价格
$0.08▲ 1.3%
市值
$5.02M▲ 1.3%
24小时成交量
$6,338
难度
16.65T▲ 0.8%
全网算力
282.1 GH/s▲ 5.9%
区块奖励
17.25 IRON
出块时间
59s
最新高度
1806216
Sep 14Sep 19Sep 21
Sep 14Sep 19Sep 21
Sep 14Sep 19Sep 21
Sep 14Sep 19Sep 21
IRON 挖矿计算器
使用您的算力挖掘 IRON 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 | 0.37306992 IRON | $0.02900.00000036 BTC | $0 | $0.0290 |
| 每天 | 8.9537 IRON | $0.69700.00000857 BTC | $0 | $0.6970 |
| 每周 | 62.6757 IRON | $4.87900.00005998 BTC | $0 | $4.8790 |
| 每月 | 268.6103 IRON | $20.910.00025707 BTC | $0 | $20.91 |
IRON 交易所
按 24 小时成交量排序的主要市场,已过滤异常值。
| 交易所 | 交易对 | 价格 | 24小时成交量 |
|---|---|---|---|
| IRON/USDT | $0.08 | $2,348 |
IRON 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 |
|---|---|---|---|---|
| $0.76 | $0.38 | 40/100 | ||
| $0.93 | $0.29 | 40/100 | ||
| $0.57 | $0.22 | 40/100 | ||
| $0.50 | $0.17 | 40/100 | ||
| $0.40 | $0.16 | 40/100 | ||
| $0.40 | $0.15 | 40/100 | ||
| $0.30 | $0.13 | 40/100 | ||
| $0.25 | $0.12 | 40/100 | ||
| $0.58 | $0.11 | 40/100 | ||
| $0.41 | $0.10 | 40/100 |
IRON 矿池
| 矿池 | 费率 | 支付方式 | 最低支付 |
|---|---|---|---|
| 1% | PPS+ | 0.5 IRON | |
| 0% | SOLO | 0.1 IRON | |
| 1% | PPLNS | 1 IRON |
关于 Iron Fish 的常见问题
How long does it take to mine 1 IRON?
At the current Iron Fish difficulty it would take about 2 hours with Nvidia CMP 170HX.
What is the current Iron Fish difficulty?
Iron Fish network difficulty is currently 16.65T.
What is the current Iron Fish network hashrate?
Iron Fish network hashrate is currently 282.1 GH/s.
Which hardware can mine Iron Fish?
Iron Fish runs on the FishHash algorithm: the strongest listed devices today are Nvidia CMP 170HX (GPU). See the full ranking in the hardware table above.
Is Iron Fish worth mining?
With Nvidia CMP 170HX, IRON currently earns $0.76 per day before electricity. Run your own numbers in the calculator above.
网络数据更新于 4 min agoMethodology