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MiningBoard Pro
XELISHASHV3 $0.0095/KH/d TARIRANDOMX $0.0293/KH/d QHASH $0.0001/MH/d DYNEXSOLVE $0.0109/KH/d OCTOPUS $0.0131/MH/d NEXAPOW $0.0016/MH/d ABELHASH $0.0000/MH/d MEOWPOW $0.0053/MH/d KARLSENHASHV2 $3.1170/GH/d KAWPOW $0.0045/MH/d CUCKAROO29 $0.0188/H/d ETCHASH $0.0005/MH/d XELISHASHV3 $0.0095/KH/d TARIRANDOMX $0.0293/KH/d QHASH $0.0001/MH/d DYNEXSOLVE $0.0109/KH/d OCTOPUS $0.0131/MH/d NEXAPOW $0.0016/MH/d ABELHASH $0.0000/MH/d MEOWPOW $0.0053/MH/d KARLSENHASHV2 $3.1170/GH/d KAWPOW $0.0045/MH/d CUCKAROO29 $0.0188/H/d ETCHASH $0.0005/MH/d
Butterfly Labs · ASIC · Sha256 · RELEASED AUG 2013

Butterfly Labs BFL Single SC — AI Rental

Profit /day
$-1.44
Income /day
$0.00
0.00000003 BTC/day
Cost $1.44 @ $0.1/kWh
Hashrate
60Gh/s
Sha256
Power · Efficiency
600.0W
10.00 j/Gh

Butterfly Labs BFL Single SC doesn't currently have fresh profitability data.

1 minute ago Similar miners ↓

Live GPU rental rates for the Butterfly Labs BFL Single SC on Vast.ai, RunPod, io.net and other AI compute marketplaces. Each row shows host-net daily income after platform fees, current utilization, and your payback period at $0.1/kWh.

Frequently asked

About the Butterfly Labs BFL Single SC

Can the Butterfly Labs BFL Single SC earn from AI rental?

No. The Butterfly Labs BFL Single SC is a mining ASIC — it has no general-purpose compute cores and cannot run AI workloads. AI rental is a GPU-only income mode.

Which AI rental marketplace pays the most for the Butterfly Labs BFL Single SC?

We track Vast.ai, RunPod, io.net and other AI compute marketplaces. The table above ranks them by daily host take-home for the Butterfly Labs BFL Single SC after platform fees. Best provider varies by GPU model — datacenter cards like H100/B200 usually clear higher on Vast.ai, while consumer cards often utilize better on RunPod.

How long until the Butterfly Labs BFL Single SC pays back via AI rental?

At $0.1/kWh and current host-net rates, the ROI calculator on this site projects payback months for the Butterfly Labs BFL Single SC. Real payback depends on AI demand cycles — utilization swings with the broader compute market, so plan around 30–80% utilization rather than 100%.