MinerstatMinerstat

AMD BC-160

GPU

최고 코인

KLS

최고 순수익

$0.22/ 일7d median $0.22 · $0.10 to $0.77

최고 해시레이트

131.6 MH/sAutolykos2

소비 전력

93 W

수익 계산기

내 전기 요금과 보유 대수를 기준으로 이 기기에서 오늘 가장 수익성 높은 코인을 계산합니다.

* $0.08/kWh 기준. 세부 조정: 채굴 계산기.

전기 요금 민감도

전기 요금별로 이 장비가 벌어들이는 금액입니다. 각 구간마다 최적의 코인을 다시 선택합니다.

KLSNEXAbreak-even $0.178$0$0.06$0.13$0.19$0.25$0.40/day$0
electricity price, $/kWh
  • $0.03/kWh

    $0.33

    KLS
  • $0.05/kWh

    $0.29

    KLS
  • $0.06/kWh

    $0.26

    KLS
  • $0.08/kWh

    $0.22

    KLS
  • $0.10/kWh

    $0.17

    KLS
  • $0.12/kWh

    $0.13

    KLS

Worth switching?

KLS is currently 38.6% more profitable than Iron Fish on this device, and has been ahead for 23 h 55 min.

IRON$0.16/dayKLS$0.22/dayHigh confidence · 75/100

Switching has its own costs (downtime, payout thresholds, pool minimums). This compares gross mining economics only. See what the estimate does not model.

알고리즘별 성능

측정된 해시레이트와 소비 전력이며, 이 수치가 사이트의 모든 수익 수치의 기반이 됩니다.

알고리즘해시레이트소비 전력효율업데이트
Autolykos2131.6 MH/s93 W1.415 MH/s/W2026-09-30
Etchash71 MH/s130 W546.2 kH/s/W2026-09-30
Ethash71 MH/s130 W546.2 kH/s/W2026-10-01
FishHash43.68 MH/s93 W469.7 kH/s/W2026-10-01
KarlsenHash43.68 MH/s93 W469.7 kH/s/W2026-10-01
FiroPoW22.14 MH/s91 W243.3 kH/s/W2026-09-30
KAWPOW20.22 MH/s90 W224.7 kH/s/W2026-10-01
NexaPoW9.52 MH/s20 W476 kH/s/W2026-10-01

AMD BC-160 자주 묻는 질문

What hashrate does the AMD BC-160 reach?

The BC-160 reaches 131.6 MH/s on Autolykos2 at around 93 W, and is benchmarked on 8 algorithms in total.

How much can the AMD BC-160 earn per day?

At current network conditions the BC-160 earns about $0.40 per day mining KLS, for $0.22 of profit at $0.08/kWh. Use the calculator above for your own electricity price.

Is the AMD BC-160 still worth it?

Mining stays profitable with the BC-160 as long as your electricity costs less than $0.18 per kWh at today's rates.

Which coins can the AMD BC-160 mine?

The most profitable options today are KLS, IRON, FIRO — the full ranking is in the profit calculator above.

벤치마크 업데이트 9 d agoMethodology