English
German
Hungarian
Dutch
Spanish
French
Italian
Czech
Polish
Greek
Aleo ASIC Miner Profitability Calculator
Read more Read less
Read more Read less
| Model |
Profitability
Profit
|
|---|---|
|
Goldshell Byte
zkSNARK · 5.5MH/s
|
$-0.12
/day
|
|
Goldshell AE Card
zkSNARK · 5.5MH/s
|
$-0.12
/day
|
|
IceRiver AE0
zkSNARK · 60MH/s
|
$-0.14
/day
|
|
Goldshell AE-BOX
zkSNARK · 37MH/s
|
$-0.66
/day
|
|
IceRiver AE1 Lite
zkSNARK · 300MH/s
|
$-0.69
/day
|
|
IceRiver AE1 Lite
zkSNARK · 250MH/s
|
$-0.74
/day
|
|
Goldshell AE-BOX Pro
zkSNARK · 44MH/s
|
$-0.84
/day
|
|
Goldshell AE Box 2
zkSNARK · 54MH/s
|
$-0.97
/day
|
|
IceRiver AE3
zkSNARK · 600MH/s
|
$-1.39
/day
|
|
IceRiver AE2
zkSNARK · 720MH/s
|
$-1.86
/day
|
|
Goldshell E-AE1M
zkSNARK · 230MH/s
|
$-3.64
/day
|
|
IceRiver AE3
zkSNARK · 2GH/s
|
$-4.75
/day
|
|
Goldshell AE Max II
zkSNARK · 540MH/s
|
$-5.66
/day
|
|
Goldshell AE Max
zkSNARK · 360MH/s
|
$-6.02
/day
|
Our cutting-edge mining calculator offers comprehensive insights across all major cryptocurrency algorithms, helping users easily identify the most profitable options for their specific hardware. The algorithm data is continuously refreshed to keep pace with the dynamic crypto mining industry, providing accurate evaluations based on real-time profitability statistics and overall market activity. This empowers users to make well-informed choices that reflect the latest mining conditions and algorithm performance.
Aleo ASICs do not hash. They prove.
A ledger can hold a secret that speaks through a proof, and the proof echoes the ledger. zkSNARKs are Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge that let one party prove a claim without revealing the hidden data. They preserve privacy and reduce bandwidth, while keeping verification simple for nodes that check blocks. Proofs are short, and many verifiers run in near constant time relative to the statement size. In cryptocurrencies they enable fully encrypted transactions that still satisfy consensus rules and remain auditable at the protocol level. Zcash demonstrates this with shielded transfers that conceal sender, recipient, and amount while staying valid on chain. Mining in zkSNARK-oriented systems shifts effort from hash puzzles to the generation and checking of cryptographic proofs. Verification is lightweight for validators, but proof construction is compute heavy and memory sensitive. Provers run large multi-scalar multiplications, number theoretic transforms, and pairings on elliptic curves such as BLS12-381. High performance rigs favor GPUs for parallel MSM and NTT kernels, while FPGAs and ASICs improve energy efficiency on fixed elliptic curve pipelines. Engineers push throughput with pipelining, warp-level parallelism, vector instructions, and low-latency memory architectures. Custom firmware, tuned schedulers, and tight memory layouts reduce cache misses and kernel stalls during long proving jobs. Stable thermals, reliable power delivery, and error-correcting memory protect correctness under sustained load. Profitability depends on proof throughput per watt, local electricity costs, network difficulty, block issuance, fees, and downtime risk. Real-time calculators can estimate returns for a given rig by modeling proof rate, power draw, and difficulty trends. Future work aims to cut overhead in proof aggregation and recursive verification so blocks carry fewer bytes and verify faster. Systems adopt universal or updatable setups and multi-party ceremonies to limit the risk from trusted setup parameters. Compromise of those parameters could enable counterfeit proofs, so transparency and ceremony design matter. New proof systems such as Groth16, Plonk, and Halo2 streamline circuits and widen application scope, while KZG commitments keep proofs succinct. Alternative designs like zkSTARKs remove the trusted setup and improve resistance to quantum attacks, though proofs are often larger and verifier costs differ. As privacy coins and apps gain traction, builders seek architectures that balance compute, memory bandwidth, and communication so the outer network and the inner proof engine move in step.
Four words that replace the usual mining vocabulary
Read the table with these in mind and the zkSNARK rows stop looking odd.
Prover
What an Aleo "miner" really is. Instead of guessing hashes, the machine solves cryptographic puzzles and submits zero-knowledge proofs; the network rewards valid proofs.
Proof rate
The Aleo equivalent of hashrate: how many puzzle solutions the hardware produces per second. The table lists it in the hashrate column so provers can be compared like any other ASIC.
Coinbase puzzle
The changing puzzle every prover works on. Its difficulty adjusts with total proof rate, so more provers on the network means a smaller share of the reward for each.
Credits
Aleo's native token, paid to provers in proportion to the proofs they contribute. Prices, block time and emission feed the daily figures in the table just like any coin.
- Network proof rate
- 27.40 TH/s
- Difficulty
- 138.74 M
- Block reward
- 103.9972 ALEO
- Block time
- 14 s
Because the coinbase puzzle changes and proof difficulty tracks the total proof rate, an Aleo prover's income behaves more like a share of a pool than like a lottery ticket. That makes the daily figure in the table steadier than on small proof-of-work chains, but it also means every new prover generation dilutes the old ones quickly.
The hardware market is younger than for SHA-256 or Scrypt: prover ASICs arrived only after Aleo's mainnet, and the gap between generations is still large. Check the release date column before comparing two provers on efficiency alone.
About zkSNARK proving on Aleo
zkSNARKs (Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge) are cryptographic proofs that let a prover demonstrate a statement’s truth without revealing the underlying data, enabling on-chain validation with off-chain secrecy-an austere mechanism that hides the fearful complexity of private computation beneath a calm, verifiable surface; in blockchains like Aleo and Zcash, this permits fully encrypted, “shielded” transactions to be validated under consensus rules while concealing sender, recipient, and amount, shifting the work of “mining” from puzzle-solving to generating and verifying proofs with minimal on-chain footprint, typically small proofs and fast verification; under the hood, modern zkSNARKs rely on arithmetization (e.g., R1CS or PLONK-style circuits), polynomial commitments, fast Fourier transforms, and heavy elliptic-curve operations such as multi-scalar multiplications over pairing-friendly curves like BN254 or BLS12-381, making GPUs, FPGAs, and sometimes ASICs valuable for accelerating FFTs and MSMs, improving throughput and energy efficiency while battling memory bandwidth and latency bottlenecks with techniques like Pippenger’s method, batched MSM, and careful parallelization; although verification is lightweight, proof generation is intensive and historically requires a trusted setup to create a structured reference string-mitigated by multi-party ceremonies (e.g., Powers of Tau), updatable setups, and universal SRS schemes (Sonic, Marlin, PLONK), yet still a point of systemic caution because compromised parameters could poison the well; ongoing research targets recursion for scalable rollups and private smart contracts, SNARK-friendly hashes (Poseidon, Rescue) for circuit efficiency, and alternative transparent systems such as zkSTARKs, which remove trusted setup and lean on hash-based security with stronger post-quantum resilience at the cost of larger proofs; in practice, the strategic frontier is clear: squeeze latency from proof generation, compress memory flows, and preserve privacy at scale so that the network can know enough to trust-while knowing almost nothing at all.
Aleo prover hardware, answered
Mining profitability in your pocket
Every ASIC miner, GPU and coin from the site, with live profit, ROI and your own electricity rate — free, no account needed, on iOS and Android.
